\n\n \n\n \n\n \n \n\n \n\n \n \n\n \n\n \n

\n generated by\n \n $\"bibbase.org\"\n$ \n \n

\n \n\n

\n\n

\n \n Group by\n \n \n
- \n Year\n
- \n Author\n
- \n Type\n
- \n Keyword\n
- \n Downloads\n
\n
\n \n \n \n \n
- \n \n Expand/Collapse All\n \n
- \n \n Download BibTeX\n \n
- \n \n RSS Feed\n \n
\n

\n\n\n

\n\n Excellent! Next you can\n create a new website with this list, or\n embed it in an existing web page by copying & pasting\n any of the following snippets.\n\n

\n JavaScript\n (easiest)\n

\n            <script src=\"https://bibbase.org/show?bib=https%3A%2F%2Fraw.githubusercontent.com%2Fssanner%2Fssanner.github.io%2Fmaster%2FSanner_CV.bib&jsonp=1&jsonp=1\"></script>\n

\n\n PHP\n

\n            <?php\n            $contents = file_get_contents(\"https://bibbase.org/show?bib=https%3A%2F%2Fraw.githubusercontent.com%2Fssanner%2Fssanner.github.io%2Fmaster%2FSanner_CV.bib&jsonp=1\");\n            print_r($contents);\n            ?>\n

\n\n iFrame\n (not recommended)\n

\n            <iframe src=\"https://bibbase.org/show?bib=https%3A%2F%2Fraw.githubusercontent.com%2Fssanner%2Fssanner.github.io%2Fmaster%2FSanner_CV.bib&jsonp=1\"></iframe>\n

\n\n

\n For more details see the documention.\n

\n\n

\n\n This is a preview! To use this list on your own web site\n or create a new web site from it,\n create a free account. The file will be added\n and you will be able to edit it in the File Manager.\n We will show you instructions once you've created your account.\n

\n\n

To the site owner:

\n\n

Action required! Mendeley is changing its\n API. In order to keep using Mendeley with BibBase past April\n 14th, you need to:\n

renew the authorization for BibBase on Mendeley, and
update the BibBase URL\n in your page the same way you did when you initially set up\n this page.\n

\n\n

\n \n \n Fix it now\n

\n\n

\n\n\n

\n \n \n

\n \n 2026\n \n \n (20)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n Blocked Gibbs meets Diffusion Transformers: Unsupervised Learning for Constraint Optimization.\n \n \n \n\n\n \n Xu, Y.; Li, W.; Wang, X.; Sanner, S.; and Khalil, E. B.\n\n\n \n\n\n\n In Proceedings of the 40th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-26), Sydney, Australia, 2026. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:neurips26a,\n\tauthor = {Yudong Xu and Wenhao Li and Xiaoyu Wang and Scott Sanner and Elias Boutros Khalil},\n\tyear = {2026},\n\ttitle = {Blocked Gibbs meets Diffusion Transformers: Unsupervised Learning for Constraint Optimization},\n\tbooktitle = {Proceedings of the 40th Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-26})},\n\taddress = {Sydney, Australia}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Plan2Sense: Open-World Task Planning in Epistemic States via Interleaved Ontic and Sensing Actions.\n \n \n \n\n\n \n Liu, X.; Toroghi, A.; Liang, J.; Pesaranghader, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 40th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-26), Sydney, Australia, 2026. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:neurips26b,\n\tauthor = {Xiaotian Liu and Armin Toroghi and Jiazhou Liang and Ali Pesaranghader and Scott Sanner},\n\tyear = {2026},\n\ttitle = {Plan2Sense: Open-World Task Planning in Epistemic States via Interleaved Ontic and Sensing Actions},\n\tbooktitle = {Proceedings of the 40th Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-26})},\n\taddress = {Sydney, Australia}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n ReBOL: Retrieval via Bayesian Optimization with Batched LLM Relevance Observations and Query Reformulation.\n \n \n \n \n\n\n \n Korikov, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP-26), Budapest, Hungary, October 2026. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"ReBOL:$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 11 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:emnlp26,\n    title = "{ReBOL}: Retrieval via Bayesian Optimization with Batched LLM Relevance Observations and Query Reformulation",\n    author = "Anton Korikov and Scott Sanner",\n    booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing ({EMNLP}-26)",\n    month = oct,\n    year = "2026",\n    address = "Budapest, Hungary",\n    publisher = "Association for Computational Linguistics",\n    url_paper = {https://ssanner.github.io/papers/emnlp26_rebol.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n ACPO: Agent-Chained Policy Optimization for Multi-Agent Reinforcement Learning.\n \n \n \n \n\n\n \n Matsunaga, D. E.; Na, J.; Guntara, T. W.; Sanner, S.; Poupart, P.; Lee, J.; and Kim, K.\n\n\n \n\n\n\n In Proceedings of the 3rd Reinforcement Learning Conference (RLC), Montreal, Canada, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"ACPO:$ arxiv\n \n \n \n $\"ACPO:$ code\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:rlc26, \n  author = {Daiki E. Matsunaga and Junho Na and Tri Wahyu Guntara and Scott Sanner and Pascal Poupart and Jongmin Lee and Kee-Eung Kim}, \n  title = {ACPO: Agent-Chained Policy Optimization for Multi-Agent Reinforcement Learning}, \n  booktitle = {Proceedings of the 3rd Reinforcement Learning Conference ({RLC})}, \n  year = {2026},\n  address = "Montreal, Canada",\n  url_arxiv = {https://arxiv.org/abs/2606.30072},\n  url_code = {https://github.com/dematsunaga/agent-chained-policy-optimization}\n} \n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models.\n \n \n \n \n\n\n \n Toroghi, A.; Kalarde, F. M.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-26), Melbourne, Australia, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"CommonWhy:$ paper\n \n \n \n $\"CommonWhy:$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 21 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir26,\n\ttitle = {CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models},\n\tauthor = {Armin Toroghi and Faeze Moradi Kalarde and Scott Sanner},\n\tbooktitle = {Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval ({SIGIR}-26)},\n\taddress = {Melbourne, Australia},\n\tyear = {2026},\n\turl_paper = {https://ssanner.github.io/papers/sigir26_commonwhy.pdf},\n\turl_github = {https://github.com/faezemoradik/CommonWhyDataset}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n VOGUE: A Multimodal Dataset for Conversational Recommendation in Fashion.\n \n \n \n \n\n\n \n Guo, D.; Sun, M.; Jiang, Y.; Liang, J.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the the 34th ACM Conference on User Modeling, Adaptation and Personalization (UMAP-26), Gothenburg, Sweden, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"VOGUE:$ paper\n \n \n \n $\"VOGUE:$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 21 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:umap26,\n  author = {David Guo and Minqi Sun and Yilun Jiang and Jiazhou Liang and Scott Sanner},\n  title = {VOGUE: A Multimodal Dataset for Conversational Recommendation in Fashion},\n  year = {2026},\n  booktitle = {Proceedings of the the 34th ACM Conference on User Modeling, Adaptation and Personalization ({UMAP-26})},\n  address = {Gothenburg, Sweden},\n  url_paper = {https://ssanner.github.io/papers/umap26_vogue.pdf},\n  url_github = {https://github.com/D3Mlab/vogue}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Structure-Aware Graph Hypernetworks for Neural Program Synthesis.\n \n \n \n \n\n\n \n Li, W.; Xu, Y.; Khalil, E. B.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the International Conference on Learning Representations (ICLR-26), Rio de Janeiro, Brazil, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"Structure-Aware$ pdf\n \n \n \n $\"Structure-Aware$ poster\n \n \n \n $\"Structure-Aware$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 32 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:iclr26a,\n\t    title = {Structure-Aware Graph Hypernetworks for Neural Program Synthesis},\n\t    author = {Wenhao Li and Yudong Xu and Elias Boutros Khalil and Scott Sanner},\n\t    booktitle = {Proceedings of the International Conference on Learning Representations ({ICLR}-26)},\n\t    address = {Rio de Janeiro, Brazil},\n\t    year = {2026},\n        url_pdf = {https://ssanner.github.io/papers/iclr26_ghnps.pdf},\n        url_poster = {https://ssanner.github.io/papers/iclr26_ghnps_poster.pdf},\n\t    url_url = {https://iclr.cc/virtual/2026/poster/10006668}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Improving Set Function Approximation with Quasi-Arithmetic Neural Networks.\n \n \n \n \n\n\n \n Tokar, T.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the International Conference on Learning Representations (ICLR-26), Rio de Janeiro, Brazil, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"Improving$ paper\n \n \n \n $\"Improving$ arxiv\n \n \n \n $\"Improving$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 21 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:iclr26b,\n\t    title = {Improving Set Function Approximation with Quasi-Arithmetic Neural Networks},\n\t    author = {Tomas Tokar and Scott Sanner},\n\t    booktitle = {Proceedings of the International Conference on Learning Representations ({ICLR}-26)},\n\t    address = {Rio de Janeiro, Brazil},\n\t    year = {2026},\n        url_paper = {https://ssanner.github.io/papers/iclr26_quann.pdf},\n\t    url_arxiv = {https://www.arxiv.org/abs/2602.04941},\n\t    url_url = {https://iclr.cc/virtual/2026/poster/10010201}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Natural Language PDDL (NL-PDDL) for Open-world Goal-oriented Commonsense Regression Planning in Embodied AI.\n \n \n \n \n\n\n \n Liu, X.; Toroghi, A.; Liang, J.; Courtis, D.; Li, R.; Pesaranghader, A.; Kim, J.; Sadhu, T.; Jeon, H.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the International Conference on Learning Representations (ICLR-26), Rio de Janeiro, Brazil, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"Natural$ pdf\n \n \n \n $\"Natural$ poster\n \n \n \n $\"Natural$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 43 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:iclr26c,\n\t    title = {Natural Language PDDL ({NL-PDDL}) for Open-world Goal-oriented Commonsense Regression Planning in Embodied AI},\n\t    author = {Xiaotian Liu and Armin Toroghi and Jiazhou Liang and David Courtis and Ruiwen Li and Ali Pesaranghader and Jaehong Kim and Tanmana Sadhu and Hyejeong Jeon and Scott Sanner},\n\t    booktitle = {Proceedings of the International Conference on Learning Representations ({ICLR}-26)},\n\t    address = {Rio de Janeiro, Brazil},\n\t    year = {2026},\n        url_pdf = {https://ssanner.github.io/papers/iclr26_nlpddl.pdf},\n        url_poster = {https://ssanner.github.io/papers/iclr26_nlpddl_poster.pdf},\n\t    url_url = {https://iclr.cc/virtual/2026/poster/10007784}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Semantic XPath: Structured Agentic Memory Access for Conversational AI.\n \n \n \n \n\n\n \n Liu, Y. S.; Wu, R.; Gallagher, L.; Liang, J.; Toroghi, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics: Systems Demonstrations (ACL-26), San Diego, USA, 2026. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Semantic$ paper\n \n \n \n $\"Semantic$ poster\n \n \n \n $\"Semantic$ demo\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 23 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:acl26d,\n      title={Semantic XPath: Structured Agentic Memory Access for Conversational AI}, \n      author={Yifan Simon Liu and Ruifan Wu and Liam Gallagher and Jiazhou Liang and Armin Toroghi and Scott Sanner},\n      booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics: Systems Demonstrations ({ACL}-26)},\n      address = {San Diego, USA},\n      publisher = {Association for Computational Linguistics},\n      year={2026},\n      url_paper={https://ssanner.github.io/papers/acl26_semxpath.pdf}, \n      url_poster={https://ssanner.github.io/papers/acl26_semxpath_poster.pdf}, \n      url_demo={https://semanticxpathchat.com/}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Evaluating Scene-based In-Situ Item Labeling for Immersive Conversational Recommendation.\n \n \n \n \n\n\n \n Liang, J.; Liu, Y. S.; Guo, D.; Sun, M.; Jiang, Y.; and Sanner, S.\n\n\n \n\n\n\n In Findings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL-26), San Diego, USA, 2026. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluating$ paper\n \n \n \n $\"Evaluating$ poster\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 24 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:acl26a,\n      title={Evaluating Scene-based In-Situ Item Labeling for Immersive Conversational Recommendation}, \n      author={Jiazhou Liang and Yifan Simon Liu and David Guo and Minqi Sun and Yilun Jiang and Scott Sanner},\n      booktitle = {Findings of the 64th Annual Meeting of the Association for Computational Linguistics ({ACL}-26)},\n      address = {San Diego, USA},\n      publisher = {Association for Computational Linguistics},\n      year={2026},\n      url_paper={https://ssanner.github.io/papers/acl26_scenexr.pdf}, \n      url_poster={https://ssanner.github.io/papers/acl26_scenexr_poster.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Active Learning with Gaussian Processes Guided by LLM Relevance Scoring for Dense Passage Retrieval.\n \n \n \n \n\n\n \n Kim, J.; Korikov, A.; Liang, J.; Cui, J.; Liu, Y. S.; Wen, Q.; Zhao, M.; and Sanner, S.\n\n\n \n\n\n\n In Findings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL-26), San Diego, USA, 2026. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n \n $\"Bayesian$ poster\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:acl26b,\n      title={Bayesian Active Learning with Gaussian Processes Guided by LLM Relevance Scoring for Dense Passage Retrieval}, \n      author={Junyoung Kim and Anton Korikov and Jiazhou Liang and Justin Cui and Yifan Simon Liu and Qianfeng Wen and Mark Zhao and Scott Sanner},\n      booktitle = {Findings of the 64th Annual Meeting of the Association for Computational Linguistics ({ACL}-26)},\n      address = {San Diego, USA},\n      publisher = {Association for Computational Linguistics},\n      year={2026},\n      url_paper={https://ssanner.github.io/papers/acl26_bagel.pdf}, \n      url_poster={https://ssanner.github.io/papers/acl26_bagel_poster.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Multimodal Item Scoring for Natural Language Recommendation via Gaussian Process Regression with LLM Relevance Judgments.\n \n \n \n \n\n\n \n Liu, Y. S.; Wen, Q.; Liang, J.; Zhao, M.; Cui, J.; Korikov, A.; Toroghi, A.; Kim, J.; and Sanner, S.\n\n\n \n\n\n\n In Findings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL-26), San Diego, USA, 2026. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Multimodal$ paper\n \n \n \n $\"Multimodal$ poster\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 17 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:acl26c,\n      title={Multimodal Item Scoring for Natural Language Recommendation via Gaussian Process Regression with LLM Relevance Judgments}, \n      author={Yifan Simon Liu and Qianfeng Wen and Jiazhou Liang and Mark Zhao and Justin Cui and Anton Korikov and Armin Toroghi and Junyoung Kim and Scott Sanner},\n      booktitle = {Findings of the 64th Annual Meeting of the Association for Computational Linguistics ({ACL}-26)},\n      address = {San Diego, USA},\n      publisher = {Association for Computational Linguistics},\n      year={2026},\n      url_paper={https://ssanner.github.io/papers/acl26_gpllmrec.pdf}, \n      url_poster={https://ssanner.github.io/papers/acl26_gpllmrec_poster.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Large Neighborhood Search meets Iterative Neural Constraint Heuristics.\n \n \n \n \n\n\n \n Xu, Y.; Li, W.; Sanner, S.; and Khalil, E. B.\n\n\n \n\n\n\n In Proceedings of the 23rd International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-26), Rabat, Morocco, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"Large$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 16 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cpaior26,\n  title = {Large Neighborhood Search meets Iterative Neural Constraint Heuristics},\n  author = {Yudong Xu and Wenhao Li and Scott Sanner and Elias Boutros Khalil},\n  booktitle = {Proceedings of the 23rd International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-26)}, \n  address = {Rabat, Morocco},\n  year = {2026},\n  url_paper = {https://ssanner.github.io/papers/cpaior26_neurallns.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Efficient Modality Translation via Arbitrary Conditioning and Wasserstein Regularization.\n \n \n \n \n\n\n \n Tokar, T.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 40th AAAI Conference on Artificial Intelligence (AAAI-26), Singapore, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"Efficient$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 19 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai26a,\n\tauthor = {Tomas Tokar and Scott Sanner},\n\ttitle = {Efficient Modality Translation via Arbitrary Conditioning and Wasserstein Regularization},\n\tyear = {2026},\n\tbooktitle = {Proceedings of the 40th {AAAI} Conference on Artificial Intelligence ({AAAI-26})},\n\taddress = {Singapore},\n\turl_paper = {https://ssanner.github.io/papers/aaai26_macwae.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Near-optimal Linear Predictive Clustering in Non-separable Spaces via MIP and QPBO Reductions.\n \n \n \n \n\n\n \n Liang, J.; Khurram, H.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 40th AAAI Conference on Artificial Intelligence (AAAI-26), Singapore, 2026. \n \n\n\n\n
\n\n\n\n \n \n $\"Near-optimal$ paper\n \n \n \n $\"Near-optimal$ poster\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 31 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai26b,\n\tauthor = {Jiazhou Liang and Hassan Khurram and Scott Sanner},\n\ttitle = {Near-optimal Linear Predictive Clustering in Non-separable Spaces via MIP and QPBO Reductions},\n\tyear = {2026},\n\tbooktitle = {Proceedings of the 40th {AAAI} Conference on Artificial Intelligence ({AAAI-26})},\n\taddress = {Singapore},\n\turl_paper = {https://ssanner.github.io/papers/aaai26_optlpc.pdf},\n\turl_poster = {https://ssanner.github.io/papers/aaai26_optlpc_poster.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Generalized Multi-Hop Downstream Traffic Pressure for Heterogeneous Perimeter Control.\n \n \n \n \n\n\n \n Li, X.; Wang, X.; Smirnov, I.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n IET Intelligent Transport Systems, 20(1): e70340. 2026.\n \n\n\n\n
\n\n\n\n \n \n $\"Generalized$ preprint\n \n \n \n $\"Generalized$ url\n \n \n \n $\"Generalized$ doi\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:iet26,\n  author = {Xiaocan Li and Xiaoyu Wang and Ilia Smirnov and Scott Sanner and Baher Abdulhai},\n  title = {Generalized Multi-Hop Downstream Traffic Pressure for Heterogeneous Perimeter Control},\n  journal = {IET Intelligent Transport Systems},\n  year = {2026},\n  volume = {20},\n  number = {1}, \n  pages = {e70340},\n  url_preprint = {https://ssanner.github.io/papers/ietits26_multihoppc.pdf},\n  url_url = {https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/itr2.70340},\n  url_doi = {http://dx.doi.org/10.1049/itr2.70340}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Recommendation with Generative Models.\n \n \n \n \n\n\n \n Deldjoo, Y.; He, Z.; McAuley, J.; Korikov, A.; Sanner, S.; Ramisa, A.; Vidal, R.; Sathiamoorthy, M.; Kasrizadeh, A.; Milano, S.; and Ricci, F.\n\n\n \n\n\n\n Foundations and Trends in Information Retrieval, 20(1-2): 1-176. 05 2026.\n \n\n\n\n
\n\n\n\n \n \n $\"Recommendation$ abstract\n \n \n \n $\"Recommendation$ pdf\n \n \n \n $\"Recommendation$ doi\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:fntir26,\n    author = {Deldjoo, Yashar and He, Zhankui and McAuley, Julian and Korikov, Anton and Sanner, Scott and Ramisa, Arnau and Vidal, René and Sathiamoorthy, Maheswaran and Kasrizadeh, Atoosa and Milano, Silvia and Ricci, Francesco},\n    title = {Recommendation with Generative Models},\n    journal = {Foundations and Trends in Information Retrieval},\n    volume = {20},\n    number = {1-2},\n    pages = {1-176},\n    year = {2026},\n    month = {05},\n    issn = {1554-0669},\n    doi = {10.1108/FTINR-06-2025-0109},\n    url_abstract = {https://www.emerald.com/ftinr/article-abstract/20/1-2/1/1379964/Recommendation-with-generative-models}, \n    url_pdf = {https://www.emerald.com/ftinr/article-pdf/20/1-2/1/11676543/ftinr-06-2025-0109en.pdf},\n    url_doi = {https://doi.org/10.1108/FTINR-06-2025-0109}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Retrieval-Augmented Generation for Medical Question Answering on a Heart Failure Dataset: Performance Analysis.\n \n \n \n \n\n\n \n Zhang, S.; Phan, E.; Velmovitsky, P. E.; Pham, Q.; and Sanner, S.\n\n\n \n\n\n\n JMIR Formative Research, 10: e84932. Feb 2026.\n \n\n\n\n
\n\n\n\n \n \n $\"Retrieval-Augmented$ url\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:jmir26,\n  title = {Retrieval-Augmented Generation for Medical Question Answering on a Heart Failure Dataset: Performance Analysis},\n  author = {Shiran Zhang and Evelyn Phan and Pedro Elkind Velmovitsky and Quynh Pham and Scott Sanner},\n  journal = {JMIR Formative Research},\n  year = {2026},\n  month = {Feb},\n  day = {26},\n  volume = {10},\n  pages = {e84932},\n  doi = {10.2196/84932},\n  url_url = {https://formative.jmir.org/2026/1/e84932},\n  doi = {10.2196/84932}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Mapping Social Change: A Unified Framework for Temporal Clustering.\n \n \n \n \n\n\n \n Liang, J.; Tosanwumi, J.; Fosse, E.; Silver, D.; and Sanner, S.\n\n\n \n\n\n\n Sociological Methods & Research,00491241251396789. 2026.\n \n\n\n\n
\n\n\n\n \n \n $\"Mapping$ url\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 12 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:smr26,\n  author = {Jiazhou Liang and Jolomi Tosanwumi and Ethan Fosse and Daniel Silver and Scott Sanner},\n  title = {Mapping Social Change: A Unified Framework for Temporal Clustering},\n  journal = {Sociological Methods \\& Research},\n  pages = {00491241251396789},\n  year = {2026},\n  url_url = {https://doi.org/10.1177/00491241251396789},\n  doi = {10.1177/00491241251396789}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2025\n \n \n (16)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n ActiveVOO: Value of Observation Guided Active Knowledge Acquisition for Open-World Embodied Lifted Regression Planning.\n \n \n \n \n\n\n \n Liu, X.; Pesaranghader, A.; Kim, J.; Sadhu, T.; Jeon, H.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 39th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-25), San Diego, USA, 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"ActiveVOO:$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:neurips25,\n\tauthor = {Xiaotian Liu and Ali Pesaranghader and Jaehong Kim and Tanmana Sadhu and Hyejeong Jeon and Scott Sanner},\n\tyear = {2025},\n\ttitle = {ActiveVOO: Value of Observation Guided Active Knowledge Acquisition for Open-World Embodied Lifted Regression Planning},\n\tbooktitle = {Proceedings of the 39th Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-25})},\n\taddress = {San Diego, USA},\n\turl_paper = {https://ssanner.github.io/papers/neurips25_activevoo.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n MA-DPR: Manifold-aware Distance Metrics for Dense Passage Retrieval.\n \n \n \n \n\n\n \n Liu, Y. S.; Wen, Q.; Zhao, M.; Liang, J.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP-25), pages 31073–31091, Suzhou, China, November 2025. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"MA-DPR:$ paper\n \n \n \n $\"MA-DPR:$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 10 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:emnlp25a,\n    title = "{MA}-{DPR}: Manifold-aware Distance Metrics for Dense Passage Retrieval",\n    author = "Yifan Simon Liu and Qianfeng Wen and Mark Zhao and Jiazhou Liang and Scott Sanner",\n    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing ({EMNLP}-25)",\n    month = nov,\n    year = "2025",\n    address = "Suzhou, China",\n    publisher = "Association for Computational Linguistics",\n    url_paper = {https://ssanner.github.io/papers/emnlp25_madpr.pdf}, \n    url_url = "https://aclanthology.org/2025.emnlp-main.1582/",\n    pages = "31073--31091"\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Batched Self-Consistency Improves LLM Relevance Assessment and Ranking.\n \n \n \n \n\n\n \n Korikov, A.; Du, P.; Sanner, S.; and Rekabsaz, N.\n\n\n \n\n\n\n In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP-25), pages 32675–32691, Suzhou, China, November 2025. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Batched$ paper\n \n \n \n $\"Batched$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:emnlp25b,\n    title = "Batched Self-Consistency Improves {LLM} Relevance Assessment and Ranking",\n    author = "Anton Korikov and Pan Du and Scott Sanner and Navid Rekabsaz",\n    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing ({EMNLP}-25)",\n    month = nov,\n    year = "2025",\n    address = "Suzhou, China",\n    publisher = "Association for Computational Linguistics",\n    url_paper = {https://ssanner.github.io/papers/emnlp25_batchllm.pdf}, \n    url_url = "https://aclanthology.org/2025.emnlp-main.1661/",\n    pages = "32675--32691"\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction.\n \n \n \n \n\n\n \n Xu, Y.; Li, W.; Sanner, S.; and Khalil, E. B.\n\n\n \n\n\n\n In Proceedings of the 42nd International Conference on Machine Learning (ICML-25), Vancouver, Canada, 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"Self-Supervised$ paper\n \n \n \n $\"Self-Supervised$ poster\n \n \n \n $\"Self-Supervised$ arxiv\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 31 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icml25a,\n  title = {Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction},\n  author = {Yudong Xu and Wenhao Li and Scott Sanner and Elias Boutros Khalil},\n  booktitle = {Proceedings of the 42nd International Conference on Machine Learning ({ICML-25})},\n  address = {Vancouver, Canada},\n  year = {2025},\n  url_paper = {https://ssanner.github.io/papers/icml25_sstranscsp.pdf},\n  url_poster = {https://ssanner.github.io/papers/icml25_sstranscsp_poster.pdf},\n  url_arxiv = {https://arxiv.org/abs/2502.15794}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens.\n \n \n \n \n\n\n \n Jeong, J.; Wang, X.; Wang, J.; Sanner, S.; and Poupart, P.\n\n\n \n\n\n\n In Proceedings of the 42nd International Conference on Machine Learning (ICML-25), Vancouver, Canada, 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"Reflect-then-Plan:$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 21 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icml25b,\n  title = {Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens},\n  author = {Jihwan Jeong and Xiaoyu Wang and Jingmin Wang and Scott Sanner and Pascal Poupart},\n  booktitle = {Proceedings of the 42nd International Conference on Machine Learning ({ICML-25})},\n  address = {Vancouver, Canada},\n  year = {2025},\n  url_paper = {https://ssanner.github.io/papers/icml25_refplan.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Open-World Planning via Lifted Regression with LLM-Inferred Affordances for Embodied Agents.\n \n \n \n \n\n\n \n Liu, X.; Pesaranghader, A.; Li, H.; Sukcharoenchaikul, P.; Kim, J.; Sadhu, T.; Jeon, H.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL-25), 2025. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Open-World$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 16 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:acl25a,\n  author       = {Xiaotian Liu and Ali Pesaranghader and Hanze Li and Punyaphat Sukcharoenchaikul and Jaehong Kim and Tanmana Sadhu and Hyejeong Jeon and Scott Sanner},\n  title        = {Open-World Planning via Lifted Regression with LLM-Inferred Affordances for Embodied Agents},\n  booktitle    = {Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics ({ACL}-25)},\n  publisher    = {Association for Computational Linguistics},\n  year         = {2025},\n  url_paper = {https://ssanner.github.io/papers/acl25_llmregress.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Q-STRUM Debate: Query-Driven Contrastive Summarization for Recommendation Comparison.\n \n \n \n \n\n\n \n Saad, G.; and Sanner, S.\n\n\n \n\n\n\n In Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL-25), 2025. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Q-STRUM$ paper\n \n \n \n $\"Q-STRUM$ arxiv\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 33 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:acl25b,\n  author       = {George-Kirollos Saad and Scott Sanner},\n  title        = {Q-STRUM Debate: Query-Driven Contrastive Summarization for Recommendation Comparison},\n  booktitle    = {Findings of the 63rd Annual Meeting of the Association for Computational Linguistics ({ACL}-25)},\n  publisher    = {Association for Computational Linguistics},\n  year         = {2025},\n  url_paper    = {https://ssanner.github.io/papers/acl25_qstrum.pdf},\n  url_arxiv    = {https://arxiv.org/abs/2502.12921}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n LLM-based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases.\n \n \n \n \n\n\n \n Toroghi, A.; Pesaranghader, A.; Sadhu, T.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the International Conference on Learning Representations (ICLR-25), Singapore, 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"LLM-based$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 46 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:iclr25,\n\t    title = {LLM-based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases},\n\t    author = {Armin Toroghi and Ali Pesaranghader and Tanmana Sadhu and Scott Sanner},\n\t    booktitle = {Proceedings of the International Conference on Learning Representations ({ICLR}-25)},\n\t    address = {Singapore},\n\t    year = {2025},\n\t    url_paper = {https://ssanner.github.io/papers/iclr25_llmth.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bounded-Error Policy Optimization for Mixed Discrete-Continuous MDPs via Constraint Generation in Nonlinear Programming.\n \n \n \n \n\n\n \n Gimelfarb, M.; Taitler, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 22nd International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-25), Melbourne, Australia, 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"Bounded-Error$ preprint 2 col\n \n \n \n $\"Bounded-Error$ arxiv\n \n \n \n $\"Bounded-Error$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 52 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cpaior25,\n\ttitle = {Bounded-Error Policy Optimization for Mixed Discrete-Continuous MDPs via Constraint Generation in Nonlinear Programming},\n\tauthor = {Michael Gimelfarb and Ayal Taitler and Scott Sanner},\n\tbooktitle = {Proceedings of the 22nd International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-25)}, \n\taddress = {Melbourne, Australia},\n\tyear = {2025},\n\turl_preprint_2_col = {https://ssanner.github.io/papers/cpaior25_cgpo2col.pdf},\n\turl_arxiv = {https://arxiv.org/abs/2401.12243v2},\n\turl_github = {https://github.com/pyrddlgym-project/pyRDDLGym/tree/GurobiCompilerBranch}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n CoLoTa: A Dataset for Entity-based Commonsense Reasoning over Long-Tail Knowledge.\n \n \n \n \n\n\n \n Toroghi, A.; Guo, W.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-25), Padova, Italy, 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"CoLoTa:$ arxiv\n \n \n \n $\"CoLoTa:$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 13 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir25,\n\ttitle = {CoLoTa: A Dataset for Entity-based Commonsense Reasoning over Long-Tail Knowledge},\n\tauthor = {Armin Toroghi and Willis Guo and Scott Sanner},\n\tbooktitle = {Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval ({SIGIR}-25)},\n\taddress = {Padova, Italy},\n\tyear = {2025},\n\turl_arxiv = {https://arxiv.org/abs/2504.14462},\n\turl_github = {https://github.com/D3Mlab/CoLoTa}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n ModelDiff: Symbolic Dynamic Programming for Model-Aware Policy Transfer in Deep Q-Learning.\n \n \n \n \n\n\n \n Liu, X.; Jeong, J.; Taitler, A.; Gimelfarb, M.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), Philadelphia, USA, 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"ModelDiff:$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai25a,\n\tauthor = {Xiaotian Liu and Jihwan Jeong and Ayal Taitler and Michael Gimelfarb and Scott Sanner},\n\ttitle = {ModelDiff: Symbolic Dynamic Programming for Model-Aware Policy Transfer in Deep Q-Learning},\n\tyear = {2025},\n\tbooktitle = {Proceedings of the 39th {AAAI} Conference on Artificial Intelligence ({AAAI-25})},\n\taddress = {Philadelphia, USA},\n\turl_paper = {https://ssanner.github.io/papers/aaai25_modeldiff.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n ICE-T: Interactions-aware Cross-column Contrastive Embedding for Heterogeneous Tabular Datasets.\n \n \n \n \n\n\n \n Tokar, T.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), Philadelphia, USA, 2025. \n \n\n\n\n
\n\n\n\n \n \n $\"ICE-T:$ paper\n \n \n \n $\"ICE-T:$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai25b,\n\tauthor = {Tomas Tokar and Scott Sanner},\n\ttitle = {ICE-T: Interactions-aware Cross-column Contrastive Embedding for Heterogeneous Tabular Datasets},\n\tyear = {2025},\n\tbooktitle = {Proceedings of the 39th {AAAI} Conference on Artificial Intelligence ({AAAI-25})},\n\taddress = {Philadelphia, USA},\n\turl_paper = {https://ssanner.github.io/papers/aaai25_icet.pdf},\n\turl_github = {https://github.com/tomastokar/ICET}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Getting Ready for Deployment: Transformer-Enabled Robust Adaptive Traffic Signal Control.\n \n \n \n \n\n\n \n Wang, X.; Smirnov, I.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n In 28th IEEE International Intelligent Transportation Systems Conference (ITSC-25), Gold Coast, Australia, 2025. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Getting$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:itsc25,\n\tauthor    = {Xiaoyu Wang and Ilia Smirnov and Scott Sanner and Baher Abdulhai},\n\ttitle     = {Getting Ready for Deployment: Transformer-Enabled Robust Adaptive Traffic Signal Control},\n\tbooktitle = {28th {IEEE} International Intelligent Transportation Systems Conference ({ITSC}-25)},\n\tpublisher = {{IEEE}},\n\taddress   = {Gold Coast, Australia},\n\tyear      = {2025},\n    url_paper = {https://ssanner.github.io/papers/itsc25_emarlintrans.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Tackling the Abstraction and Reasoning Corpus with Vision Transformers: the Importance of 2D Representation, Positions, and Objects.\n \n \n \n \n\n\n \n Li, W.; Xu, Y.; Khalil, E. B.; and Sanner, S.\n\n\n \n\n\n\n Transactions on Machine Learning Research (TMLR). April 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Tackling$ paper\n \n \n \n $\"Tackling$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:tmlr25,\n\ttitle = {Tackling the Abstraction and Reasoning Corpus with Vision Transformers: the Importance of 2D Representation, Positions, and Objects},\n\tauthor = {Wenhao Li and Yudong Xu and Elias Boutros Khalil and Scott Sanner},\n\tjournal = {Transactions on Machine Learning Research ({TMLR})},\n\tissn = {2835-8856},\n\tyear = {2025},\n\tmonth = {April},\n\turl_paper = {https://openreview.net/pdf?id=Al72Fp0rCg},\n\turl_url = {https://openreview.net/forum?id=Al72Fp0rCg}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Multi-Hop Upstream Anticipatory Traffic Signal Control With Deep Reinforcement Learning.\n \n \n \n \n\n\n \n Li, X.; Wang, X.; Smirnov, I.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n IEEE Open Journal of Intelligent Transportation Systems, 6: 554-567. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Multi-Hop$ url\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:ojits25,\n  author={Xiaocan Li and Xiaoyu Wang and Ilia Smirnov and Scott Sanner and Baher Abdulhai},\n  journal={IEEE Open Journal of Intelligent Transportation Systems}, \n  title={Multi-Hop Upstream Anticipatory Traffic Signal Control With Deep Reinforcement Learning}, \n  year={2025},\n  volume={6},\n  pages={554-567},\n  url_url={https://ieeexplore.ieee.org/document/10970747},\n  doi={10.1109/OJITS.2025.3562757}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n tscluster: A Python package for the optimal temporal clustering framework.\n \n \n \n \n\n\n \n Tosanwumi, J.; Liang, J.; Silver, D.; Fosse, E.; and Sanner, S.\n\n\n \n\n\n\n Environment and Planning B, 52(4): 1014-1024. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"tscluster:$ url\n \n \n \n $\"tscluster:$ github\n \n \n \n $\"tscluster:$ doc\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 10 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:epb25,\n  author = {Jolomi Tosanwumi and Jiazhou Liang and Daniel Silver and Ethan Fosse and Scott Sanner},\n  title = {tscluster: A {Python} package for the optimal temporal clustering framework},\n  journal = {Environment and Planning B},\n  volume = {52},\n  number = {4},\n  pages = {1014-1024},\n  year = {2025},\n  url_url = {https://journals.sagepub.com/doi/full/10.1177/23998083241293833},\n  url_github = {https://github.com/tscluster-project/tscluster},\n  url_doc = {https://tscluster.readthedocs.io/en/latest/index.html},\n  doi = {10.1177/23998083241293833}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2024\n \n \n (14)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering.\n \n \n \n \n\n\n \n Toroghi, A.; Guo, W.; Pour, M. M. A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP-24), Miami, USA, 2024. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Right$ paper\n \n \n \n $\"Right$ arxiv\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 47 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:emnlp24a,\n  title = {Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering},\n  author = {Armin Toroghi and Willis Guo and Mohammad Mahdi Abdollah Pour and Scott Sanner},\n  booktitle = {Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing ({EMNLP-24})},\n  year = {2024},\n  address = {Miami, USA}, \n  publisher = {Association for Computational Linguistics},\n  url_paper = {https://ssanner.github.io/papers/emnlp24_r3.pdf},\n  url_arxiv = {https://arxiv.org/abs/2403.01390}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Verifiable, Debuggable, and Repairable Commonsense Logical Reasoning via LLM-based Theory Resolution.\n \n \n \n \n\n\n \n Toroghi, A.; Guo, W.; Pesaranghader, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP-24), Miami, USA, 2024. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Verifiable,$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 28 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:emnlp24b,\n  title={Verifiable, Debuggable, and Repairable Commonsense Logical Reasoning via {LLM}-based Theory Resolution},\n  author={Armin Toroghi and Willis Guo and Ali Pesaranghader and Scott Sanner},\n  booktitle = {Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing ({EMNLP-24})},\n  year = {2024},\n  address = {Miami, USA}, \n  publisher = {Association for Computational Linguistics},\n  url_paper = {https://ssanner.github.io/papers/emnlp24_llmtres.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation.\n \n \n \n \n\n\n \n Austin, D. E.; Korikov, A.; Toroghi, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of 18th ACM Conference on Recommender Systems (RecSys-24), Bari, Italy, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n \n $\"Bayesian$ arxiv\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 34 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:recsys24,\n  title = {Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation},\n  author = {David Eric Austin and Anton Korikov and Armin Toroghi and Scott Sanner},\n  year = {2024},\n  booktitle = {Proceedings of 18th {ACM} Conference on Recommender Systems ({RecSys-24})},\n  address = {Bari, Italy},\n  url_paper = {https://ssanner.github.io/papers/recsys24_pebol.pdf},\n  url_arxiv = {https://arxiv.org/abs/2405.00981} \n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys).\n \n \n \n \n\n\n \n Deldjoo, Y.; He, Z.; McAuley, J. J.; Korikov, A.; Sanner, S.; Ramisa, A.; Vidal, R.; Sathiamoorthy, M.; Kasirzadeh, A.; and Milano, S.\n\n\n \n\n\n\n In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-24), Barcelona, Spain, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n \n $\"A$ arxiv\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 11 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:kdd24,\n  author       = {Yashar Deldjoo and\n                  Zhankui He and\n                  Julian J. McAuley and\n                  Anton Korikov and\n                  Scott Sanner and\n                  Arnau Ramisa and\n                  Ren{\\'{e}} Vidal and\n                  Maheswaran Sathiamoorthy and\n                  Atoosa Kasirzadeh and\n                  Silvia Milano},\n  title        = {A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)},\n  booktitle    = {Proceedings of the 30th {ACM} {SIGKDD} Conference on Knowledge Discovery\n                  and Data Mining ({KDD-24})},\n  address      = {Barcelona, Spain},\n  year         = {2024},\n  url_paper = {https://ssanner.github.io/papers/kdd24_genairec.pdf},\n  url_arxiv = {https://arxiv.org/abs/2404.00579}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking.\n \n \n \n \n\n\n \n Cui, J.; Dicarlantonio, K.; Kemper, S.; Lin, K.; Tang, D.; Korikov, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-24), Washington D.C., USA, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Retrieval-Augmented$ paper\n \n \n \n $\"Retrieval-Augmented$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 101 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir24,\n\ttitle = {Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking},\n\tauthor = {Justin Cui and Kai Dicarlantonio and Sara Kemper and Kathy Lin and Danjie Tang and Anton Korikov and Scott Sanner},\n\tbooktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval ({SIGIR}-24)},\n\taddress = {Washington D.C., USA},\n\tyear = {2024},\n\turl_paper = {https://ssanner.github.io/papers/sigir24_llmrec.pdf},\n\turl_github = {https://github.com/D3Mlab/llm-convrec}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n JaxPlan and GurobiPlan: Optimization Baselines for Replanning in Discrete and Mixed Discrete-Continuous Probabilistic Domains.\n \n \n \n \n\n\n \n Gimelfarb, M.; Taitler, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 34th Conference on Automated Planning and Scheduling (ICAPS-24), Banff, Canada, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"JaxPlan$ paper\n \n \n \n $\"JaxPlan$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 30 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icaps24,\n\tauthor = {Michael Gimelfarb and Ayal Taitler and Scott Sanner},\n\ttitle = {{JaxPlan} and {GurobiPlan}: Optimization Baselines for Replanning in Discrete and Mixed Discrete-Continuous Probabilistic Domains},\n\tbooktitle = {Proceedings of the 34th Conference on Automated Planning and Scheduling ({ICAPS-24})},\n\taddress = {Banff, Canada},\n\tyear = {2024},\n \turl_paper = {https://ssanner.github.io/papers/icaps24_jaxplan.pdf},\n\turl_github = {https://github.com/mike-gimelfarb/ICAPS2024Exp}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Inference with Complex Knowledge Graph Evidence.\n \n \n \n \n\n\n \n Toroghi, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, Canada, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n \n $\"Bayesian$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 56 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai24,\n\tauthor = {Armin Toroghi and Scott Sanner},\n\ttitle = {Bayesian Inference with Complex Knowledge Graph Evidence},\n\tyear = {2024},\n\tbooktitle = {Proceedings of the 38th {AAAI} Conference on Artificial Intelligence ({AAAI-24})},\n\taddress = {Vancouver, Canada},\n\turl_paper = {https://ssanner.github.io/papers/aaai24_bikg.pdf},\n\turl_github = {https://github.com/atoroghi/BIKG}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Gaussian Process Optimization for Adaptable Multi-Objective Text Generation using Linearly-Weighted Language Models.\n \n \n \n \n\n\n \n Pour, M. M. A.; Pesaranghader, A.; Cohen, E.; and Sanner, S.\n\n\n \n\n\n\n In Findings of the North American Chapter of the Association for Computational Linguistics (NAACL-24), Mexico City, Mexico, Jun 2024. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"Gaussian$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 14 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:naacl24,\n    title = {Gaussian Process Optimization for Adaptable Multi-Objective Text Generation using Linearly-Weighted Language Models},\n    author = {Mohammad Mahdi Abdollah Pour and Ali Pesaranghader and Eldan Cohen and Scott Sanner},\n    booktitle = {Findings of the North American Chapter of the Association for Computational Linguistics ({NAACL-24})},\n    month = {Jun},\n    year = {2024},\n    address = {Mexico City, Mexico},\n    publisher = {Association for Computational Linguistics},\n    url_paper = {https://ssanner.github.io/papers/naacl24_gpllm.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n User Experience and The Role of Personalization in Critiquing-Based Conversational Recommendation.\n \n \n \n \n\n\n \n Rana, A.; Sanner, S.; Bouadjenek, M. R.; Dicarlantonio, R.; and Farmaner, G.\n\n\n \n\n\n\n ACM Transactions on the Web (TWeb), 18(4): 43:1–43:21. Nov 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"User$ url\n \n \n \n $\"User$ paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:tweb24,\n  author = {Arpit Rana and Scott Sanner and Mohamed Reda Bouadjenek and Ron Dicarlantonio and Gary Farmaner},\n  title = {User Experience and The Role of Personalization in Critiquing-Based Conversational Recommendation},\n  publisher = {Association for Computing Machinery},\n  address = {New York, NY, USA},\n  year = {2024},\n  month = {Nov},\n  volume = {18},\n  number = {4},\n  pages = {43:1--43:21},\n  issn = {1559-1131},  \n  url_url = {https://doi.org/10.1145/3597499},\n  url_paper = {https://rbouadjenek.github.io/papers/TWEB-22-0072.pdf},\n  doi = {10.1145/3597499},\n  journal = {ACM Transactions on the Web (TWeb)}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n eMARLIN+: Addressing Partial Observability to Promote Traffic Signal Coordination by Leveraging Historical Information.\n \n \n \n \n\n\n \n Wang, X.; Taitler, A.; Smirnov, I.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n Trans. Intell. Transport. Sys., 25(12): 21380–21392. December 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"eMARLIN+:$ url\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:transits24,\n  author = {Xiaoyu Wang and Ayal Taitler and Ilia Smirnov and Scott Sanner and Baher Abdulhai},\n  title = {eMARLIN+: Addressing Partial Observability to Promote Traffic Signal Coordination by Leveraging Historical Information},\n  year = {2024},\n  issue_date = {Dec. 2024},\n  publisher = {IEEE Press},\n  volume = {25},\n  number = {12},\n  issn = {1524-9050},\n  journal = {Trans. Intell. Transport. Sys.},\n  month = dec,\n  pages = {21380–21392},\n  numpages = {13},\n  url_url = {https://ieeexplore.ieee.org/document/10700669},\n  doi = {10.1109/TITS.2024.3462951}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n eMARLIN: Distributed Coordinated Adaptive Traffic Signal Control with Topology-Embedding Propagation.\n \n \n \n \n\n\n \n Wang, X.; Taitler, A.; Smirnov, I.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n Transportation Research Record, 2678(4): 189-202. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"eMARLIN:$ url\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:trr24,\n  author = {Xiaoyu Wang and Ayal Taitler and Ilia Smirnov and Scott Sanner and Baher Abdulhai},\n  title ={eMARLIN: Distributed Coordinated Adaptive Traffic Signal Control with Topology-Embedding Propagation},\n  journal = {Transportation Research Record},\n  volume = {2678},\n  number = {4},\n  pages = {189-202},\n  year = {2024},\n  url_url = {https://journals.sagepub.com/doi/full/10.1177/03611981231184250},\n  doi = {10.1177/03611981231184250}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Network Motifs for Reasoning over Heterogeneous Unlinked Datasets.\n \n \n \n \n\n\n \n Sui, Y.; Kwan, A.; Olson, A. W.; Sanner, S.; and Silver, D. A.\n\n\n \n\n\n\n Data Mining and Knowledge Discovery (DAMI), 38: 3643–3689. August 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n \n $\"Bayesian$ github\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 10 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:dami24, \n  author = {Yi Sui and Alex Kwan and Alexander W. Olson and Scott Sanner and Daniel A. Silver},\n  title = {Bayesian Network Motifs for Reasoning over Heterogeneous Unlinked Datasets},\n  journal = {Data Mining and Knowledge Discovery ({DAMI})},\n  year = {2024},\n  volume = {38}, \n  pages = {3643–3689},\n  month = {August},\n  publisher = {Springer},\n  doi = {https://doi.org/10.1007/s10618-024-01054-7},\n  url_paper = {https://ssanner.github.io/papers/dami24_baymotif.pdf},\n  url_github = {https://github.com/D3Mlab/ppandas}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations.\n \n \n \n \n\n\n \n Xu, Y.; Li, W.; Vaezipoor, P.; Sanner, S.; and Khalil, E. B.\n\n\n \n\n\n\n Transactions on Machine Learning Research (TMLR). Feb 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"LLMs$ paper\n \n \n \n $\"LLMs$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 20 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:tmlr24,\n\ttitle = {{LLM}s and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations},\n\tauthor = {Yudong Xu and Wenhao Li and Pashootan Vaezipoor and Scott Sanner and Elias Boutros Khalil},\n\tjournal = {Transactions on Machine Learning Research ({TMLR})},\n\tissn = {2835-8856},\n\tyear = {2024},\n\tmonth = {Feb},\n\turl_paper = {https://ssanner.github.io/papers/tmlr24_llmarc.pdf},\n\turl_url = {https://openreview.net/forum?id=E8m8oySvPJ}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The 2023 International Planning Competition.\n \n \n \n \n\n\n \n Taitler, A.; Alford, R.; Espasa, J.; Behnke, G.; Fišer, D.; Gimelfarb, M.; Pommerening, F.; Sanner, S.; Scala, E.; Schreiber, D.; Segovia-Aguas, J.; and Seipp, J.\n\n\n \n\n\n\n AI Magazine, 45(2): 280-296. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ paper\n \n \n \n $\"The$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 9 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:aimag24,\n  author = {Taitler, Ayal and Alford, Ron and Espasa, Joan and Behnke, Gregor and Fišer, Daniel and Gimelfarb, Michael and Pommerening, Florian and Sanner, Scott and Scala, Enrico and Schreiber, Dominik and Segovia-Aguas, Javier and Seipp, Jendrik},\n  title = {The 2023 International Planning Competition},\n  journal = {AI Magazine},\n  volume = {45},\n  number = {2},\n  pages = {280-296},\n  year = {2024},\n  url_paper = {https://ssanner.github.io/papers/aimag24_ippc.pdf},\n  url_url = {https://onlinelibrary.wiley.com/doi/full/10.1002/aaai.12169}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2023\n \n \n (19)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n COUNT: COntrastive UNlikelihood Text Style Transfer for Text Detoxification.\n \n \n \n \n\n\n \n Pour, M. M. A.; Farinneya, P.; Bharadwaj, M.; Verma, N.; Pesaranghader, A.; and Sanner, S.\n\n\n \n\n\n\n In Findings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP-23), Singapore, 2023. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"COUNT:$ paper\n \n \n \n $\"COUNT:$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 20 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:emnlp23,\n  title = {{COUNT}: COntrastive UNlikelihood Text Style Transfer for Text Detoxification},\n  author = {Mohammad Mahdi Abdollah Pour and Parsa Farinneya and Manasa Bharadwaj and Nikhil Verma and Ali Pesaranghader and Scott Sanner},\n  booktitle = {Findings of the 2023 Conference on Empirical Methods in Natural Language Processing ({EMNLP-23})},\n  year = {2023},\n  address = {Singapore}, \n  publisher = {Association for Computational Linguistics},\n  url_paper = {https://ssanner.github.io/papers/emnlp23_count.pdf},\n  url_github = {https://github.com/D3Mlab/count-style-transfer}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences.\n \n \n \n \n\n\n \n Sanner, S.; Balog, K.; Radlinski, F.; Wedin, B.; and Dixon, L.\n\n\n \n\n\n\n In Proceedings of 17th ACM Conference on Recommender Systems (RecSys-23), Singapore, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Large$ paper\n \n \n \n $\"Large$ arxiv\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 53 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:recsys23,\n  title = {Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences},\n  author = {Scott Sanner and Krisztian Balog and Filip Radlinski and Ben Wedin and Lucas Dixon},\n  year = {2023},\n  booktitle = {Proceedings of 17th {ACM} Conference on Recommender Systems ({RecSys}-23)},\n  address = {Singapore},\n  url_paper = {https://ssanner.github.io/papers/recsys23_llmrec.pdf},\n  url_arxiv = {https://arxiv.org/abs/2307.14225} \n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization.\n \n \n \n \n\n\n \n Jeong, J.; Wang, X.; Gimelfarb, M.; Kim, H.; Abdulhai, B.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the International Conference on Learning Representations (ICLR-23), Kigali, Rwanda, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Conservative$ paper\n \n \n \n $\"Conservative$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 67 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:iclr23,\n\t    title = {Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization},\n\t    author = {Jihwan Jeong and Xiaoyu Wang and Michael Gimelfarb and Hyunwoo Kim and Baher Abdulhai and Scott Sanner},\n\t    booktitle = {Proceedings of the International Conference on Learning Representations ({ICLR}-23)},\n\t    address = {Kigali, Rwanda},\n\t    year = {2023},\n\t    url_paper = {https://ssanner.github.io/papers/iclr23_cbop.pdf},\n\t    url_github = {https://github.com/jihwan-jeong/CBOP}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects.\n \n \n \n \n\n\n \n Low, S. M.; Kumar, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 33rd Conference on Automated Planning and Scheduling (ICAPS-23), Prague, Czech Republic, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Safe$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 13 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icaps23,\n\tauthor = {Siow Meng Low and Akshat Kumar and Scott Sanner},\n\ttitle = {Safe {MDP} Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects},\n\tbooktitle = {Proceedings of the 33rd Conference on Automated Planning and Scheduling ({ICAPS-23})},\n\taddress = {Prague, Czech Republic},\n\tyear = {2023},\n \turl_paper = {https://ssanner.github.io/papers/icaps23_tempnse.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Recipe-MPR: A Test Collection for Evaluating Multi-aspect Preference-based Natural Language Retrieval.\n \n \n \n \n\n\n \n Zhang, H.; Korikov, A.; Farinneya, P.; Pour, M. M. A.; Bharadwaj, M.; Pesaranghader, A.; Huang, X. Y.; Lok, Y. X.; Wang, Z.; Jones, N.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-23), Taipei, Taiwan, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Recipe-MPR:$ paper\n \n \n \n $\"Recipe-MPR:$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 55 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir23a,\n\ttitle = {Recipe-MPR: A Test Collection for Evaluating Multi-aspect Preference-based Natural Language Retrieval},\n\tauthor = {Haochen Zhang and Anton Korikov and Parsa Farinneya and Mohammad Mahdi Abdollah Pour and Manasa Bharadwaj and Ali Pesaranghader and Xi Yu Huang and Yi Xin Lok and Zhaoqi Wang and Nathan Jones and Scott Sanner},\n\tbooktitle = {Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval ({SIGIR}-23)},\n\taddress = {Taipei, Taiwan},\n\tyear = {2023},\n\turl_paper = {https://ssanner.github.io/papers/sigir23_recipempr.pdf},\n\turl_github = {https://github.com/D3Mlab/Recipe-MPR}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Knowledge-driven Critiquing with Indirect Evidence.\n \n \n \n \n\n\n \n Toroghi, A.; Floto, G.; Tang, Z.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-23), Taipei, Taiwan, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n \n $\"Bayesian$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 32 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir23b,\n\ttitle = {Bayesian Knowledge-driven Critiquing with Indirect Evidence},\n\tauthor = {Armin Toroghi and Griffin Floto and Zhenwei Tang and Scott Sanner},\n\tbooktitle = {Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval ({SIGIR}-23)},\n\taddress = {Taipei, Taiwan},\n\tyear = {2023},\n\turl_paper = {https://ssanner.github.io/papers/sigir23_bcie.pdf},\n\turl_github = {https://github.com/atoroghi/BCIE}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval.\n \n \n \n \n\n\n \n Pour, M. M. A.; Farinneya, P.; Toroghi, A.; Korikov, A.; Pesaranghader, A.; Sajed, T.; Bharadwaj, M.; Mavrin, B.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 45th European Conference on IR Research (ECIR-23), Dublin, Ireland, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Self-Supervised$ paper\n \n \n \n $\"Self-Supervised$ github\n \n \n \n $\"Self-Supervised$ data\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 34 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ecir23,\n\tauthor    = {Mohammad Mahdi Abdollah Pour and Parsa Farinneya and Armin Toroghi and Anton Korikov and Ali Pesaranghader and Touqir Sajed and Manasa Bharadwaj and Borislav Mavrin and Scott Sanner},\n\ttitle     = {Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval},\n\tbooktitle = {Proceedings of the 45th European Conference on {IR} Research ({ECIR-23})},\n\taddress   = {Dublin, Ireland},\n\tyear      = {2023},\n\turl_paper = {https://ssanner.github.io/papers/ecir23_rir.pdf},\n\turl_github = {https://github.com/D3Mlab/rir},\n\turl_data = {https://github.com/D3Mlab/rir_data}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n DiffuDetox: A Mixed Diffusion Model for Text Detoxification.\n \n \n \n \n\n\n \n Floto, G.; Pour, M. M. A.; Farinneya, P.; Tang, Z.; Pesaranghader, A.; Bharadwaj, M.; and Sanner, S.\n\n\n \n\n\n\n In Findings of the Association for Computational Linguistics: ACL-23, pages 7566–7574, 2023. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n $\"DiffuDetox:$ url\n \n \n \n $\"DiffuDetox:$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:acl23,\n  author       = {Griffin Floto and\n                  Mohammad Mahdi Abdollah Pour and\n                  Parsa Farinneya and\n                  Zhenwei Tang and\n                  Ali Pesaranghader and\n                  Manasa Bharadwaj and\n                  Scott Sanner},\n  title        = {DiffuDetox: {A} Mixed Diffusion Model for Text Detoxification},\n  booktitle    = {Findings of the Association for Computational Linguistics: {ACL}-23},\n  pages        = {7566--7574},\n  publisher    = {Association for Computational Linguistics},\n  year         = {2023},\n  url_url      = {https://aclanthology.org/2023.findings-acl.478},\n  url_paper    = {https://aclanthology.org/2023.findings-acl.478.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus.\n \n \n \n \n\n\n \n Xu, Y.; Khalil, E. B.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI-23), Washington D.C., USA, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Graphs,$ paper\n \n \n \n $\"Graphs,$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 74 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai23a,\n\tauthor = {Yudong Xu and Elias B. Khalil and Scott Sanner},\n\ttitle = {Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus},\n\tyear = {2023},\n\tbooktitle = {Proceedings of the 37th {AAAI} Conference on Artificial Intelligence ({AAAI-23})},\n\taddress = {Washington D.C., USA},\n\turl_paper = {https://ssanner.github.io/papers/aaai23_arga.pdf},\n\turl_github = {https://github.com/khalil-research/ARGA-AAAI23}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Scalable and Globally Optimal Generalized L1 k-center Clustering via Constraint Generation in Mixed Integer Linear Programming.\n \n \n \n \n\n\n \n Chembu, A.; Sanner, S.; Khurram, H.; and Kumar, A.\n\n\n \n\n\n\n In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI-23), Washington D.C., USA, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Scalable$ paper\n \n \n \n $\"Scalable$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 52 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai23b,\n\tauthor = {Aravinth Chembu and Scott Sanner and Hassan Khurram and Akshat Kumar},\n\ttitle = {Scalable and Globally Optimal Generalized L1 k-center Clustering via Constraint Generation in Mixed Integer Linear Programming},\n\tyear = {2023},\n\tbooktitle = {Proceedings of the 37th {AAAI} Conference on Artificial Intelligence ({AAAI-23})},\n\taddress = {Washington D.C., USA},\n\turl_paper = {https://ssanner.github.io/papers/aaai23_kcenters.pdf},\n\turl_github = {https://github.com/Aravinthck/Optimal-KCenters}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Scalable and Near-Optimal Epsilon-tube Clusterwise Regression.\n \n \n \n \n\n\n \n Chembu, A.; Sanner, S.; and Khalil, E.\n\n\n \n\n\n\n In Proceedings of the 20th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-23), Nice, France, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Scalable$ paper\n \n \n \n $\"Scalable$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cpaior23a,\n\ttitle = {Scalable and Near-Optimal Epsilon-tube Clusterwise Regression},\n\tauthor = {Aravinth Chembu and Scott Sanner and Elias Khalil},\n\tbooktitle = {Proceedings of the 20th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-23)}, \n\taddress = {Nice, France},\n\tyear = {2023},\n\turl_paper = {https://ssanner.github.io/papers/cpaior23_etcr.pdf},\n\turl_github = {https://github.com/Aravinthck/CLR-epsTube}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination.\n \n \n \n \n\n\n \n Jeong, J.; Sanner, S.; and Kumar, A.\n\n\n \n\n\n\n In Proceedings of the 20th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-23), Nice, France, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n \n $\"A$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 21 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cpaior23b,\n\ttitle = {A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination}, \n\tauthor = {Jihwan Jeong and Scott Sanner and Akshat Kumar},\n\tbooktitle = {Proceedings of the 20th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-23)}, \n\taddress = {Nice, France},\n\tyear = {2023},\n\turl_paper = {https://ssanner.github.io/papers/cpaior23_dblpsve.pdf},\n\turl_github = {https://github.com/jihwan-jeong/xaddpy/tree/main/examples/dblp}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Towards Dialogue Modeling Beyond Text.\n \n \n \n \n\n\n \n Wu, T.; Zhou, Y.; Ling, W.; Yang, H.; Veloso, J.; Sun, L.; Huang, R.; Guimaraes, N.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-23), Rhodes, Greece, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 12 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icassp23,\n\ttitle = {Towards Dialogue Modeling Beyond Text},\n\tauthor = {Tongzi Wu and Yuhao Zhou and Wang Ling and Hojin Yang and Joana Veloso and Lin Sun and Ruixin Huang and Norberto Guimaraes and Scott Sanner},\n\tbooktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing ({ICASSP-23})},\n\taddress = {Rhodes, Greece},\n\tyear = {2023},\n\turl_paper = {https://ssanner.github.io/papers/icassp23_beyondtext.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Perimeter Control Using Deep Reinforcement Learning: A Model-free Approach towards Homogeneous Flow Rate Optimization.\n \n \n \n \n\n\n \n Li, X.; Mercurius, R. C.; Taitler, A.; Wang, X.; Noaeen, M.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), pages 1474–1479, 2023. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Perimeter$ arxiv\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:itsc23,\n  title={Perimeter Control Using Deep Reinforcement Learning: A Model-free Approach towards Homogeneous Flow Rate Optimization},\n  author={Xiaocan Li and Ray Coden Mercurius and Ayal Taitler and Xiaoyu Wang and Mohammad Noaeen and Scott Sanner and Baher Abdulhai},\n  booktitle={2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)},\n  pages={1474--1479},\n  year={2023},\n  organization={IEEE},\n  url_arxiv = {https://arxiv.org/abs/2305.19291}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Towards Understanding and Mitigating Unintended Biases in Language Model-driven Conversational Recommendation.\n \n \n \n \n\n\n \n Shen, T.; Li, J.; Bouadjenek, M. R.; Mai, Z.; and Sanner, S.\n\n\n \n\n\n\n Information Processing & Management, 60(1): 103139. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ url\n \n \n \n $\"Towards$ paper\n \n \n \n $\"Towards$ blog\n \n \n \n $\"Towards$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 71 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:ipm23,\n\tauthor = {Tianshu Shen and Jiaru Li and Mohamed Reda Bouadjenek and Zheda Mai and Scott Sanner},\n\ttitle = {Towards Understanding and Mitigating Unintended Biases in Language Model-driven Conversational Recommendation},\n\tjournal = {Information Processing & Management},\n\tvolume = {60},\n\tnumber = {1},\n\tpages = {103139},\n\tyear = {2023},\n\turl_url = {https://www.sciencedirect.com/science/article/pii/S0306457322002400},\n\turl_paper = {https://rbouadjenek.github.io/papers/IPM-D-22-00928.pdf},\n        url_blog = {https://tinabbb.github.io/posts/lmrec_unintended_bias/index.html},\n\turl_github = {https://github.com/TinaBBB/Unintended-Bias-LMRec}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A User-Centric Analysis of Social Media for Stock Market Prediction.\n \n \n \n \n\n\n \n Bouadjenek, M. R.; Sanner, S.; and Wu, G.\n\n\n \n\n\n\n ACM Transactions on the Web, 17: 1–22. Mar 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ url\n \n \n \n $\"A$ preprint\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 11 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:tweb23,\n\tauthor = {Mohamed Reda Bouadjenek and Scott Sanner and Ga Wu},\n\ttitle = {A User-Centric Analysis of Social Media for Stock Market Prediction},\n\tyear = {2023},\n\tpublisher = {Association for Computing Machinery},\n\taddress = {New York, NY, USA},\n\tjournal = {ACM Transactions on the Web},\n\tvolume = {17},\n\tissue = {2},\n\tpages = {1--22},\n\tmonth = {Mar},\n\turl_url = {https://dl.acm.org/doi/10.1145/3532856},\n\turl_preprint = {https://ssanner.github.io/papers/tweb22_userstockpred.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n TransCAM: Transformer Attention-Based CAM Refinement for Weakly Supervised Semantic Segmentation.\n \n \n \n \n\n\n \n Li, R.; Mai, Z.; Zhang, Z.; Jang, J.; and Sanner, S.\n\n\n \n\n\n\n Journal of Visual Communication and Image Representation, 92(C): 103800. Apr 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"TransCAM:$ url\n \n \n \n $\"TransCAM:$ preprint\n \n \n \n $\"TransCAM:$ github\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 20 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:jvcir23,\n\tauthor = {Li, Ruiwen and Mai, Zheda and Zhang, Zhibo and Jang, Jongseong and Sanner, Scott},\n\ttitle = {TransCAM: Transformer Attention-Based CAM Refinement for Weakly Supervised Semantic Segmentation},\n\tyear = {2023},\n\tpublisher = {Academic Press, Inc.},\n\taddress = {USA},\n\tvolume = {92},\n\tnumber = {C},\n\tpages = {103800},\n\tjournal = {Journal of Visual Communication and Image Representation},\n\tmonth = {Apr},\n\turl_url = {https://www.sciencedirect.com/science/article/abs/pii/S1047320323000500},\n\turl_preprint = {https://arxiv.org/pdf/2203.07239.pdf},\n\turl_github = {https://github.com/liruiwen/TransCAM}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Comparative Evaluation of Established and Contemporary Deep Learning Traffic Prediction Methods.\n \n \n \n \n\n\n \n Ting, T. J.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n In Dia, H., editor(s), Handbook on Artificial Intelligence and Transport, 1, pages 14–46. Edward Elgar Publishing, 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@incollection{sanner:handbook23a,\n  author       = {Ta Jiun Ting and Scott Sanner and Baher Abdulhai}, \n  title        = {A Comparative Evaluation of Established and Contemporary Deep Learning Traffic Prediction Methods},\n  booktitle    = {Handbook on Artificial Intelligence and Transport},\n  publisher    = {Edward Elgar Publishing},\n  year         = {2023},\n  editor       = {Hussein Dia},\n  chapter      = {1},\n  pages        = {14--46},\n  url_url      = {https://www.e-elgar.com/shop/usd/handbook-on-artificial-intelligence-and-transport-9781803929538.html}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Critical Review of Traffic Signal Control and a Novel Unified View of Reinforcement Learning and Model Predictive Control Approaches for Adaptive Traffic Signal Control.\n \n \n \n \n\n\n \n Wang, X.; Abdulhai, B.; and Sanner, S.\n\n\n \n\n\n\n In Dia, H., editor(s), Handbook on Artificial Intelligence and Transport, 17, pages 482–532. Edward Elgar Publishing, 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@incollection{sanner:handbook23b,\n  author       = {Xiaoyu Wang and Baher Abdulhai and Scott Sanner}, \n  title        = {A Critical Review of Traffic Signal Control and a Novel Unified View of Reinforcement Learning and Model Predictive Control Approaches for Adaptive Traffic Signal Control},\n  booktitle    = {Handbook on Artificial Intelligence and Transport},\n  publisher    = {Edward Elgar Publishing},\n  year         = {2023},\n  editor       = {Hussein Dia},\n  chapter      = {17},\n  pages        = {482--532},\n  url_url      = {https://www.e-elgar.com/shop/usd/handbook-on-artificial-intelligence-and-transport-9781803929538.html}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2022\n \n \n (11)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Learning to Follow Instructions in Text-Based Games.\n \n \n \n \n\n\n \n Tuli, M.; Li, A.; Vaezipoor, P.; Klassen, T.; Sanner, S.; and McIlraith, S.\n\n\n \n\n\n\n In Proceedings of the 36th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-22), New Orleans, USA, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 104 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:neurips22,\n\tauthor = {Mathieu Tuli and Andrew Li and Pashootan Vaezipoor and Toryn Klassen and Scott Sanner and Sheila McIlraith},\n\tyear = {2022},\n\ttitle = {Learning to Follow Instructions in Text-Based Games},\n\tbooktitle = {Proceedings of the 36th Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-22})},\n\taddress = {New Orleans, USA},\n\turl_paper = {https://ssanner.github.io/papers/neurips22_ltltextworld.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming.\n \n \n \n \n\n\n \n Jeong, J.; Jaggi, P.; Butler, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 39th International Conference on Machine Learning (ICML-22), Baltimore, USA, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"An$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 41 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icml22,\n\tauthor = {Jihwan Jeong and Parth Jaggi and Andrew Butler and Scott Sanner},\n\ttitle = {An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming},\n\tbooktitle = {Proceedings of the 39th International Conference on Machine Learning ({ICML-22})},\n\taddress = {Baltimore, USA},\n\tyear = {2022},\n\turl_paper = {https://ssanner.github.io/papers/icml22_emspo.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Mitigating the Filter Bubble while Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems.\n \n \n \n \n\n\n \n Gao, Z.; Shen, T.; Mai, Z.; Bouadjenek, M. R.; Waller, I.; Anderson, A.; Bodkin, R.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-22), Madrid, Spain, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"Mitigating$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 52 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir22,\n\tauthor = {Zhaolin Gao and Tianshu Shen and Zheda Mai and Mohamed Reda Bouadjenek and Isaac Waller and Ashton Anderson and Ron Bodkin and Scott Sanner},\n\ttitle = {Mitigating the Filter Bubble while Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems},\n\tbooktitle = {Proceedings of the 45th International {ACM} {SIGIR} Conference on Research and Development in Information Retrieval ({SIGIR-22})},\n\taddress   = {Madrid, Spain},\n\tyear = {2022},\n\turl_paper = {https://ssanner.github.io/papers/sigir22_tdvaecf.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Distributional Contrastive Embedding for Clarification-based Conversational Critiquing.\n \n \n \n \n\n\n \n Shen, T.; Mai, Z.; Wu, G.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 31st International Conference on the World Wide Web (WWW-22), Online, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"Distributional$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 25 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:www22,\n\tauthor = {Tianshu Shen and Zheda Mai and Ga Wu and Scott Sanner},\n\ttitle = {Distributional Contrastive Embedding for Clarification-based Conversational Critiquing},\n\tyear = {2022},\n\tbooktitle = {Proceedings of the 31st International Conference on the World Wide Web ({WWW}-22)},\n\taddress = {Online},\n\turl_paper = {https://ssanner.github.io/papers/www22_dcevae.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs.\n \n \n \n \n\n\n \n Patton, N.; Jeong, J.; Gimelfarb, M.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), Online, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 33 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai22a,\n\tauthor = {Noah Patton and Jihwan Jeong and Michael Gimelfarb and Scott Sanner},\n\ttitle = {A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs},\n\tyear = {2022},\n\tbooktitle = {Proceedings of the 36th {AAAI} Conference on Artificial Intelligence ({AAAI-22})},\n\taddress = {Online},\n\turl_paper = {https://ssanner.github.io/papers/aaai22_raptor.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs.\n \n \n \n \n\n\n \n Low, S.; Kumar, A.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), Online, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"Sample-Efficient$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai22b,\n\tauthor = {{Siow Meng} Low and Akshat Kumar and Scott Sanner},\n\ttitle = {Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs},\n\tyear = {2022},\n\tbooktitle = {Proceedings of the 36th {AAAI} Conference on Artificial Intelligence ({AAAI-22})},\n\taddress = {Online},\n\turl_paper = {https://ssanner.github.io/papers/aaai22_ilbo.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Distributional Reward Shaping: Point Estimates Are All You Need.\n \n \n \n \n\n\n \n Gimelfarb, M.; Sanner, S.; and Lee, C.\n\n\n \n\n\n\n In Proceedings of the fifth Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM-22), Providence, USA, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"Distributional$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:rldm22,\n\tauthor = {Michael Gimelfarb and Scott Sanner and Chi-Guhn Lee},\n\ttitle = {Distributional Reward Shaping: Point Estimates Are All You Need},\n\tbooktitle = {Proceedings of the fifth Multi-disciplinary Conference on Reinforcement Learning and Decision Making ({RLDM-22})},\n\taddress = {Providence, USA},\n\tyear = {2022},\n\turl_paper = {https://ssanner.github.io/papers/rldm22_distrs.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n What's in a (Data) Type? Meaningful Type Safety for Data Science.\n \n \n \n \n\n\n \n Moher, R.; Gruninger, M.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 16th International Conference on Research Challenges in Information Science (RCIS-22), Barcelona, Spain, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"What's$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:rcis22,\n\tauthor = {Riley Moher and Michael Gruninger and Scott Sanner},\n\ttitle = {What's in a (Data) Type? Meaningful Type Safety for Data Science},\n\tbooktitle = {Proceedings of the 16th International Conference on Research Challenges in Information Science ({RCIS-22})},\n\taddress = {Barcelona, Spain},\n\tyear = {2022},\n\turl_paper = {https://ssanner.github.io/papers/rcis22_datatype.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Arbitrary conditional inference in variational autoencoders via fast prior network training.\n \n \n \n \n\n\n \n Wu, G.; Domke, J.; and Sanner, S.\n\n\n \n\n\n\n Machine Learning. 2022.\n In press.\n\n\n\n
\n\n\n\n \n \n $\"Arbitrary$ url\n \n \n \n $\"Arbitrary$ preprint\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:mlj22,\n\ttitle = {Arbitrary conditional inference in variational autoencoders via fast prior network training},\n\tauthor = {Ga Wu and Justin Domke and Scott Sanner},\n\tjournal = {Machine Learning},\n\tyear = {2022},\n\tnote = {In press.},\n\turl_url = {https://link.springer.com/article/10.1007/s10994-022-06171-2},\n\turl_preprint = {https://ssanner.github.io/papers/mlj22_condinfvae.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Online Continual Learning in Image Classification: An Empirical Survey.\n \n \n \n \n\n\n \n Mai, Z.; Li, R.; Jeong, J.; Quispe, D.; Kim, H.; and Sanner, S.\n\n\n \n\n\n\n Neurocomputing, 469: 28–51. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Online$ url\n \n \n \n $\"Online$ preprint\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 16 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:neurocomp22,\n\tauthor = {Zheda Mai and Ruiwen Li and Jihwan Jeong and David Quispe and Hyunwoo Kim and Scott Sanner},\n\ttitle = {Online Continual Learning in Image Classification: An Empirical Survey},\n\tjournal   = {Neurocomputing},\n\tvolume    = {469},\n\tpages     = {28--51},\n\tyear      = {2022},\n\turl_url  = {https://www.sciencedirect.com/science/article/abs/pii/S0925231221014995},\n\turl_preprint = {https://arxiv.org/pdf/2101.10423.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Longitudinal Study of Topic Classification on Twitter.\n \n \n \n \n\n\n \n Bouadjenek, M. R.; Sanner, S.; Iman, Z.; Xie, L.; and Shi, X.\n\n\n \n\n\n\n PeerJ Computer Science. 2022.\n Accepted.\n\n\n\n
\n\n\n\n \n \n $\"A$ url\n \n \n \n $\"A$ preprint\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 19 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:peerj22,\n\ttitle = {A Longitudinal Study of Topic Classification on Twitter},\n\tauthor = {Mohamed Reda Bouadjenek and Scott Sanner and Zahra Iman and Lexing Xie and Xiaoliang Shi},\n\tjournal = {PeerJ Computer Science},\n\tyear = {2022},\n\tnote = {Accepted.},\n\turl_url = {https://peerj.com/articles/cs-991},\n\turl_preprint = {https://ssanner.github.io/papers/peerj22_longtwitter.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2021\n \n \n (16)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Risk-Aware Transfer in Reinforcement Learning using Successor Features.\n \n \n \n \n\n\n \n Gimelfarb, M.; Barreto, A.; Sanner, S.; and Lee, C.\n\n\n \n\n\n\n In Proceedings of the 35th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-21), Online, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Risk-Aware$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 10 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:neurips21a,\n\tauthor = {Michael Gimelfarb and Andre Barreto and Scott Sanner and Chi-Guhn Lee},\n\tyear = {2021},\n\ttitle = {Risk-Aware Transfer in Reinforcement Learning using Successor Features},\n\tbooktitle = {Proceedings of the 35th Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-21})},\n\taddress = {Online},\n\turl_paper = {https://ssanner.github.io/papers/neurips21_rasf.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models.\n \n \n \n \n\n\n \n Sui, Y.; Wu, G.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 35th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-21), Online, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Representer$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 25 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:neurips21b,\n\tauthor = {Yi Sui and Ga Wu and Scott Sanner},\n\tyear = {2021},\n\ttitle = {Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models},\n\tbooktitle = {Proceedings of the 35th Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-21})},\n\turl_paper = {https://ssanner.github.io/papers/neurips21_rpslje.pdf},\n\taddress = {Online}\n}  \n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts.\n \n \n \n \n\n\n \n Gimelfarb, M.; Sanner, S.; and Lee, C.\n\n\n \n\n\n\n In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence (UAI-21), Online, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Contextual$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 21 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai21,\n\tauthor = {Michael Gimelfarb and Scott Sanner and Chi-Guhn Lee},\n\ttitle = {Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts},\n\tyear = {2021},\n\tbooktitle = {Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence ({UAI-21})},\n\turl_paper = {https://ssanner.github.io/papers/uai21_contpolreuse.pdf},\n\taddress = {Online}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Experience Reuse for Learning from Multiple Demonstrators.\n \n \n \n \n\n\n \n Gimelfarb, M.; Sanner, S.; and Lee, C.\n\n\n \n\n\n\n In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Online, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 32 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai21a,\n  author = {Michael Gimelfarb and Scott Sanner and Chi-Guhn Lee},\n  year = {2021},\n  title = {Bayesian Experience Reuse for Learning from Multiple Demonstrators},\n  booktitle = {Proceedings of the 30th International Joint Conference on Artificial Intelligence ({IJCAI-21})},\n  address = {Online},\n  url_paper = {https://ssanner.github.io/papers/ijcai21_bers.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions.\n \n \n \n \n\n\n \n Jeong, J.; Jaggi, P.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Online, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 42 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai21b,\n  author = {Jihwan Jeong and Parth Jaggi and Scott Sanner},\n  year = {2021},\n  title = {Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions},\n  booktitle = {Proceedings of the 30th International Joint Conference on Artificial Intelligence ({IJCAI-21})},\n  address = {Online},\n  url_paper = {https://ssanner.github.io/papers/ijcai21_sdplptrans.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Workflow Analysis of Context-driven Conversational Recommendation.\n \n \n \n \n\n\n \n Lyu, S.; Rana, A.; Sanner, S.; and Bouadjenek, M. R.\n\n\n \n\n\n\n In Proceedings of the 30th International Conference on the World Wide Web (WWW-21), Ljubljana, Slovenia, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 144 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:www21,\n  author = {Shengnan Lyu and Arpit Rana and Scott Sanner and Mohamed Reda Bouadjenek},\n  title = {A Workflow Analysis of Context-driven Conversational Recommendation},\n  year = {2021},\n  booktitle = {Proceedings of the 30th International Conference on the World Wide Web (WWW-21)},\n  address = {Ljubljana, Slovenia},\n  url_paper = {https://ssanner.github.io/papers/www21_convrec.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Critiquing with Keyphrase Activation Vectors for VAE-based Recommender Systems.\n \n \n \n \n\n\n \n Yang, H.; Shen, T.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-21), Online, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 119 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir21,\n  author = {Hojin Yang and Tianshu Shen and Scott Sanner},\n  title = {Bayesian Critiquing with Keyphrase Activation Vectors for VAE-based Recommender Systems},\n  year = {2021},\n  booktitle = {Proceedings of the 44th International {ACM} {SIGIR} Conference on Research and Development in Information Retrieval {(SIGIR-21)}},\n  address   = {Online},\n  url_paper = {https://ssanner.github.io/papers/sigir21_tcavcrit.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Preference Elicitation with Keyphase-Item Coembeddings for Interactive Recommendation.\n \n \n \n \n\n\n \n Yang, H.; Sanner, S.; Wu, G.; and Zhou, J. P.\n\n\n \n\n\n\n In Proceedings of the the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP-21), Online, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 66 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:umap21,\n  author = {Hojin Yang and Scott Sanner and Ga Wu and Jin Peng Zhou},\n  title = {Bayesian Preference Elicitation with Keyphase-Item Coembeddings for Interactive Recommendation},\n  year = {2021},\n  booktitle = {Proceedings of the the 29th ACM Conference on User Modeling, Adaptation and Personalization ({UMAP-21})},\n  address = {Online},\n  url_paper = {https://ssanner.github.io/papers/umap21_bayprefkey.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Online Class-Incremental Continual Learning with Adversarial Shapley Value.\n \n \n \n \n\n\n \n Shim, D.; Mai, Z.; Jeong, J.; Sanner, S.; Kim, H.; and Jang, J.\n\n\n \n\n\n\n In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21), Online, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Online$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 79 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai21,\n  author = {Dongsub Shim and Zheda Mai and Jihwan Jeong and Scott Sanner and Hyunwoo Kim and Jongseong Jang},\n  title = {Online Class-Incremental Continual Learning with Adversarial Shapley Value},\n  year = {2021},\n  booktitle = {Proceedings of the 35th {AAAI} Conference on Artificial Intelligence ({AAAI-21})},\n  address = {Online},\n  url_paper = {https://ssanner.github.io/papers/aaai21_aser.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Revisiting Random Forests in a Comparative Evaluation of Graph Convolutional Neural Network Variants for Traffic Prediction.\n \n \n \n\n\n \n Ting, T. J.; Li, X.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n In 24th IEEE International Intelligent Transportation Systems Conference, ITSC 2021, pages 1259–1265, Indianapolis, USA, 2021. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:itsc21a,\n\tauthor    = {Ta Jiun Ting and\n\tXiaocan Li and\n\tScott Sanner and\n\tBaher Abdulhai},\n\ttitle     = {Revisiting Random Forests in a Comparative Evaluation of Graph Convolutional\n\tNeural Network Variants for Traffic Prediction},\n\tbooktitle = {24th {IEEE} International Intelligent Transportation Systems Conference,\n\t{ITSC} 2021},\n\tpages     = {1259--1265},\n\tpublisher = {{IEEE}},\n\taddress = {Indianapolis, USA},\n\tyear      = {2021}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Microscopic Model-Based RL Approaches for Traffic Signal Control Generalize Better than Model-Free RL Approaches.\n \n \n \n\n\n \n Jaggi, P.; Wang, X.; Carrara, N.; Sanner, S.; and Abdulhai, B.\n\n\n \n\n\n\n In 24th IEEE International Intelligent Transportation Systems Conference, ITSC 2021, pages 2525–2532, Indianapolis, USA, 2021. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:itsc21b,\n\tauthor    = {Parth Jaggi and\n\tXiaoyu Wang and\n\tNicolas Carrara and\n\tScott Sanner and\n\tBaher Abdulhai},\n\ttitle     = {Microscopic Model-Based {RL} Approaches for Traffic Signal Control\n\tGeneralize Better than Model-Free {RL} Approaches},\n\tbooktitle = {24th {IEEE} International Intelligent Transportation Systems Conference,\n\t{ITSC} 2021},\n\tpages     = {2525--2532},\n\tpublisher = {{IEEE}},\n\taddress = {Indianapolis, USA},\n\tyear      = {2021}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Development and Evaluation of Data-driven Controls for Residential Smart Thermostats.\n \n \n \n \n\n\n \n Huchuk, B.; Sanner, S.; and O'Brien, W.\n\n\n \n\n\n\n Energy and Buildings,111201. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Development$ paper\n \n \n \n $\"Development$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 9 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:enbuild21,\n  author = {Brent Huchuk and Scott Sanner and William O'Brien},\n  title = {Development and Evaluation of Data-driven Controls for Residential Smart Thermostats},\n  journal = {Energy and Buildings},\n  year = {2021},\n  pages = {111201},\n  url_paper = {https://ssanner.github.io/papers/eb21_ddrescontrol.pdf},\n  url_url = {https://doi.org/10.1016/j.enbuild.2021.111201}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Evaluation of Data-driven Thermal Models for Multi-hour Predictions using Residential Smart Thermostat Data.\n \n \n \n \n\n\n \n Huchuk, B.; Sanner, S.; and O'Brien, W.\n\n\n \n\n\n\n Journal of Building Performance Simulation. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluation$ paper\n \n \n \n $\"Evaluation$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 13 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:bps21,\n  author = {Brent Huchuk and Scott Sanner and William O'Brien},\n  title = {Evaluation of Data-driven Thermal Models for Multi-hour Predictions using Residential Smart Thermostat Data},\n  journal = {Journal of Building Performance Simulation},\n  year = {2021},\n  url_paper = {https://ssanner.github.io/papers/jbps21_resthermal.pdf},\n  url_url = {https://doi.org/10.1080/19401493.2020.1864474}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Reading the City through its Neighbourhoods: Deep text embeddings of Yelp reviews as a basis for determining similarity and change.\n \n \n \n \n\n\n \n Olson, A. W.; Calderon-Figueroa, F.; Bidian, O.; Silver, D.; and Sanner, S.\n\n\n \n\n\n\n Cities, 110: 103045. March 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Reading$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 27 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:cities21,\n  author = {Alexander W. Olson and Fernando Calderon-Figueroa and Olimpia Bidian and Daniel Silver and Scott Sanner},\n  title = {Reading the City through its Neighbourhoods: Deep text embeddings of Yelp reviews as a basis for determining similarity and change},\n  journal = {Cities},\n  volume = {110},\n  pages = {103045},\n  month = {March},\n  year = {2021},\n  url_url = {https://www.sciencedirect.com/science/article/abs/pii/S0264275120313937}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Data Analytics for Cybersecurity Enhancement of Transformer Protection.\n \n \n \n \n\n\n \n Jahromi, M. Z.; Jahromi, A. A.; Kundur, D.; Sanner, S.; and Kassouf, M.\n\n\n \n\n\n\n SIGENERGY Energy Inform. Rev., 1(1): 12–19. dec 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Data$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:eir21,\n\tauthor = {Jahromi, Martiya Zare and Jahromi, Amir Abiri and Kundur, Deepa and Sanner, Scott and Kassouf, Marthe},\n\ttitle = {Data Analytics for Cybersecurity Enhancement of Transformer Protection},\n\tyear = {2021},\n\tissue_date = {November 2021},\n\tpublisher = {Association for Computing Machinery},\n\taddress = {New York, NY, USA},\n\tvolume = {1},\n\tnumber = {1},\n\tjournal = {SIGENERGY Energy Inform. Rev.},\n\tmonth = {dec},\n\tpages = {12–19},\n\tnumpages = {8},\n\turl_url = {https://energy.acm.org/eir/data-analytics-for-cybersecurity-enhancement-of-transformer-protection/}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays.\n \n \n \n \n\n\n \n Khaw, Y. M.; Jahromi, A. A.; Arani, M. F. M.; Sanner, S.; Kundur, D.; and Kassouf, M.\n\n\n \n\n\n\n IEEE Transactions on Smart Grid, 12(3): 2554–2565. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 14 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:smartgrid21,\n\tauthor={Y. M. {Khaw} and A. A. {Jahromi} and M. F. M. {Arani} and S. {Sanner} and D. {Kundur} and M. {Kassouf}},\n\ttitle={A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays}, \n\tjournal={IEEE Transactions on Smart Grid}, \n\tvolume    = {12},\n\tnumber    = {3},\n\tpages     = {2554--2565},\n\tyear={2021},\n\turl_url = {https://ieeexplore.ieee.org/document/9270592}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2020\n \n \n (11)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n A Ranking Optimization Approach to Latent Linear Critiquing in Conversational Recommender Systems.\n \n \n \n \n\n\n \n Li, H.; Sanner, S.; Luo, K.; and Wu, G.\n\n\n \n\n\n\n In Proceedings of the 14th International ACM Conference on Recommender Systems (RecSys-20), Online, 2020. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 39 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:recsys20,\n  author    = {Hanze Li and Scott Sanner and Kai Luo and Ga Wu},\n  title     = {A Ranking Optimization Approach to Latent Linear Critiquing in Conversational Recommender Systems},\n  booktitle = {Proceedings of the 14th International {ACM} Conference on Recommender Systems {(RecSys-20)}},\n  address   = {Online},\n  year      = {2020},\n  url_paper = {https://ssanner.github.io/papers/recsys20_rankcrit.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Deep Critiquing for VAE-based Recommender Systems.\n \n \n \n \n\n\n \n Luo, K.; Yang, H.; Wu, G.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-20), Xi'an, China, 2020. \n \n\n\n\n
\n\n\n\n \n \n $\"Deep$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 140 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir20,\n  author = {Kai Luo and Hojin Yang and Ga Wu and Scott Sanner},\n  title = {Deep Critiquing for VAE-based Recommender Systems},\n  year = {2020},\n  booktitle = {Proceedings of the 43rd International {ACM} {SIGIR} Conference on Research and Development in Information Retrieval {(SIGIR-20)}},\n  address   = {Xi'an, China},\n  url_paper = {https://ssanner.github.io/papers/sigir20_cevae.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Latent Linear Critiquing for Conversational Recommender Systems.\n \n \n \n \n\n\n \n Luo, K.; Sanner, S.; Wu, G.; Li, H.; and Yang, H.\n\n\n \n\n\n\n In Proceedings of the 29th International Conference on the World Wide Web (WWW-20), Taipei, Taiwan, 2020. \n \n\n\n\n
\n\n\n\n \n \n $\"Latent$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 77 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:www20,\n  author = {Kai Luo and Scott Sanner and Ga Wu and Hanze Li and Hojin Yang},\n  title = {Latent Linear Critiquing for Conversational Recommender Systems},\n  year = {2020},\n  booktitle = {Proceedings of the 29th International Conference on the World Wide Web (WWW-20)},\n  address = {Taipei, Taiwan},\n  url_paper = {https://ssanner.github.io/papers/www20_llc.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models.\n \n \n \n \n\n\n \n Say, B.; and Sanner, S.\n\n\n \n\n\n\n Artificial Intelligence Journal (AIJ), 285: 103291. August 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Compact$ paper\n \n \n \n $\"Compact$ arxiv\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 39 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:aij20,\n  author = {Buser Say and Scott Sanner},\n  title = {Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models},\n  year = {2020},\n  volume = {285},\n  pages = {103291},\n  month = {August},\n  year = {2020},\n  journal = "Artificial Intelligence Journal ({AIJ})",\n  url_paper = {https://doi.org/10.1016/j.artint.2020.103291},\n  url_arxiv = {https://arxiv.org/abs/1811.10433}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Scalable Planning with Deep Neural Network Learned Transition Models.\n \n \n \n \n\n\n \n Wu, G.; Say, B.; and Sanner, S.\n\n\n \n\n\n\n Journal of Artificial Intelligence Research (JAIR), 68. July 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Scalable$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 57 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:jair20,\n  author = {Ga Wu and Buser Say and Scott Sanner},\n  title = {Scalable Planning with Deep Neural Network Learned Transition Models},\n  year = {2020},\n  volume = {68},\n  month = {July},\n  journal = {Journal of Artificial Intelligence Research (JAIR)},\n  url_paper = {https://ssanner.github.io/papers/jair20_tfplan.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Mitigating the Impact of Light Rail on Urban Traffic Networks using Mixed Integer Linear Programming.\n \n \n \n \n\n\n \n Guilliard, I.; Trevizan, F.; and Sanner, S.\n\n\n \n\n\n\n IET Intelligent Transport Systems, 14(6): 523–533. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Mitigating$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 20 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:iet20,\n  author = {Iain Guilliard and Felipe Trevizan and Scott Sanner},\n  title = {Mitigating the Impact of Light Rail on Urban Traffic Networks using Mixed Integer Linear Programming},\n  journal = {IET Intelligent Transport Systems},\n  year = {2020},\n  volume = {14},\n  number = {6}, \n  pages = {523--533},\n  url_paper = {https://ssanner.github.io/papers/ietits20_lightrail.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Relevance- and Interface-driven Clustering for Visual Information Retrieval.\n \n \n \n \n\n\n \n Bouadjenek, M. R.; Sanner, S.; and Du, Y.\n\n\n \n\n\n\n Information Systems, 94: 101592. December 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Relevance-$ url\n \n \n \n $\"Relevance-$ paper\n \n \n \n $\"Relevance-$ preprint\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 62 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:is20,\n  author = {Mohamed Reda Bouadjenek and Scott Sanner and Yihao Du},\n  title = {Relevance- and Interface-driven Clustering for Visual Information Retrieval},\n  journal = {Information Systems},\n  volume = {94},\n  pages = {101592},\n  year = {2020},\n  month = {December},\n  url_url = {http://www.sciencedirect.com/science/article/pii/S0306437920300752},\n  url_paper = {https://rbouadjenek.github.io/papers/IS_101592.pdf},\n  url_preprint = {https://ssanner.github.io/papers/is20_reldclust.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Classification and Regression via Integer Optimization for Neighborhood Change.\n \n \n \n \n\n\n \n Olson, A. W.; Zhang, K.; Calderon-Figueroa, F.; Yakubov, R.; Sanner, S.; Silver, D.; and Arribas-Bel, D.\n\n\n \n\n\n\n Geographical Analysis. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Classification$ url\n \n \n \n $\"Classification$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 37 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:gean20,\n  author = {Olson, Alexander W. and Zhang, Kexin and Calderon-Figueroa, Fernando and Yakubov, Ronen and Sanner, Scott and Silver, Daniel and Arribas-Bel, Dani},\n  title = {Classification and Regression via Integer Optimization for Neighborhood Change},\n  journal = {Geographical Analysis},\n  publisher = {Wiley-Blackwell},\n  year = {2020},\n  url_url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12252},\n  url_paper = {https://ssanner.github.io/papers/gean20_crionc.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Exploring smart thermostat users' schedule override behaviors and the energy consequences.\n \n \n \n \n\n\n \n Huchuk, B.; O'Brien, W.; and Sanner, S.\n\n\n \n\n\n\n Science and Technology for the Built Environment. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Exploring$ paper\n \n \n \n $\"Exploring$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 10 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:stbe20,\n  author = {Brent Huchuk and William O'Brien and Scott Sanner},\n  title = {Exploring smart thermostat users' schedule override behaviors and the energy consequences},\n  journal = {Science and Technology for the Built Environment},\n  year  = {2020},\n  publisher = {Taylor & Francis},\n  url_paper = {https://ssanner.github.io/papers/stbe20_resoverride.pdf},\n  url_url = {https://doi.org/10.1080/23744731.2020.1814668}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Comparative Evaluation of Unsupervised Deep Architectures for Intrusion Detection in Sequential Data Streams.\n \n \n \n \n\n\n \n Sovilj, D.; Budnarain, P.; Sanner, S.; Salmon, G.; and Rao, M.\n\n\n \n\n\n\n Expert Systems With Applications, 159: 113577. November 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 74 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:eswa20,\n  author = {Du\\v{s}an Sovilj and Paul Budnarain and Scott Sanner and Geoff Salmon and Mohan Rao},\n  title = {A Comparative Evaluation of Unsupervised Deep Architectures for Intrusion Detection in Sequential Data Streams},\n  journal = {Expert Systems With Applications},\n  publisher = {Elsevier},\n  year = {2020},\n  volume = {159},\n  pages = {113577},\n  month = {November},\n  url_paper = {https://ssanner.github.io/papers/eswa20_deepanomaly.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Stochastic Planning and Lifted Inference.\n \n \n \n \n\n\n \n Khardon, R.; and Sanner, S.\n\n\n \n\n\n\n In Van den Broeck, G.; Kersting, K.; Natarajan, S.; and Poole, D., editor(s), An Introduction to Lifted Probabilistic Inference, 16. MIT Press, Cambridge, MA, 2020.\n In press.\n\n\n\n
\n\n\n\n \n \n $\"Stochastic$ chapter\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@incollection{sanner:liftedinf20,\n  author       = {Roni Khardon and Scott Sanner}, \n  title        = {Stochastic Planning and Lifted Inference},\n  booktitle    = {An Introduction to Lifted Probabilistic Inference},\n  publisher    = {MIT Press},\n  year         = {2020},\n  editor       = {Guy {Van den Broeck} and Kristian Kersting and Sriraam Natarajan and David Poole},\n  chapter      = {16},\n  address      = {Cambridge, MA},\n  url_chapter  = {https://arxiv.org/abs/1701.01048},\n  note         = {In press.}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2019\n \n \n (11)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Deep Language-based Critiquing for Recommender Systems.\n \n \n \n \n\n\n \n Wu, G.; Luo, K.; Sanner, S.; and Soh, H.\n\n\n \n\n\n\n In Proceedings of the 13th ACM Conference on Recommender Systems (RecSys-19), Copenhagen, Denmark, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"Deep$ paper\n \n \n \n $\"Deep$ appendix\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 73 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:recsys19,\n  author = {Ga Wu and Kai Luo and Scott Sanner and Harold Soh},\n  title = {Deep Language-based Critiquing for Recommender Systems},\n  year = {2019},\n  booktitle = {Proceedings of the 13th {ACM} Conference on Recommender Systems ({RecSys-19})},\n  address = {Copenhagen, Denmark},\n  url_paper = {https://ssanner.github.io/papers/recsys19_deepcrit.pdf},\n  url_appendix = {https://ssanner.github.io/papers/recsys19_deepcrit_appendix.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Reward Potentials for Planning with Learned Neural Network Transition Models.\n \n \n \n \n\n\n \n Say, B.; Sanner, S.; and Thiebaux, S.\n\n\n \n\n\n\n In Proceedings of the 25th International Conference on Principles and Practice of Constraint Programming (CP-19), Stamford, USA, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"Reward$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 12 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cp19,\n  author = {Buser Say and Scott Sanner and Sylvie Thiebaux},\n  title = {Reward Potentials for Planning with Learned Neural Network Transition Models},\n  year = {2019},\n  booktitle = {Proceedings of the 25th International Conference on Principles and Practice of Constraint Programming ({CP-19})},\n  address = {Stamford, USA},\n  url_paper = {https://ssanner.github.io/papers/cp19_rewpotplan.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning.\n \n \n \n \n\n\n \n Gimelfarb, M.; Sanner, S.; and Lee, C.\n\n\n \n\n\n\n In Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI-19), Tel Aviv, Israel, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"Epsilon-BMC:$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai19,\n  author = {Michael Gimelfarb and Scott Sanner and Chi-Guhn Lee},\n  title = {Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning},\n  year = {2019},\n  booktitle = {Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence ({UAI-19})},\n  address = {Tel Aviv, Israel},\n  url_paper = {https://ssanner.github.io/papers/uai19_epsbmc.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Deep Reactive Policies for Planning in Stochastic Nonlinear Domains.\n \n \n \n \n\n\n \n Bueno, T.; de Barros, L. N.; Maua, D.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, USA, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"Deep$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 28 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai19,\n  author = {Thiago Bueno and Leliane Nunes de Barros and Denis Maua and Scott Sanner},\n  title = {Deep Reactive Policies for Planning in Stochastic Nonlinear Domains},\n  year = {2019},\n  booktitle = {Proceedings of the 33rd {AAAI} Conference on Artificial Intelligence ({AAAI-19})},\n  address = {Honolulu, USA},\n  url_paper = {https://ssanner.github.io/papers/aaai19_drp.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Noise Contrastive Estimation for One-Class Collaborative Filtering.\n \n \n \n \n\n\n \n Wu, G.; Volkovs, M.; Soon, C. L.; Sanner, S.; and Rai, H.\n\n\n \n\n\n\n In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-19), Paris, France, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"Noise$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 43 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir19a,\n  author    = {Ga Wu and Maksims Volkovs and Chee Loong Soon and Scott Sanner and Himanshu Rai},\n  title     = {Noise Contrastive Estimation for One-Class Collaborative Filtering},\n  booktitle = {Proceedings of the 42nd International {ACM} {SIGIR} Conference on Research and Development in Information Retrieval {(SIGIR-19)}},\n  address   = {Paris, France},\n  year      = {2019},\n  url_paper = {https://ssanner.github.io/papers/sigir19_nceplrec.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n One-Class Collaborative Filtering with the Queryable Variational Autoencoder.\n \n \n \n \n\n\n \n Wu, G.; Bouadjenek, M. R.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-19), Paris, France, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"One-Class$ paper\n \n \n \n $\"One-Class$ appendix\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 25 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir19b,\n  author    = {Ga Wu and Mohamed Reda Bouadjenek and Scott Sanner},\n  title     = {One-Class Collaborative Filtering with the Queryable Variational Autoencoder},\n  booktitle = {Proceedings of the 42nd International {ACM} {SIGIR} Conference on Research and Development in Information Retrieval {(SIGIR-19)}},\n  address   = {Paris, France},\n  year      = {2019},\n  url_paper = {https://ssanner.github.io/papers/sigir19_qvae.pdf},\n  url_appendix = {https://ssanner.github.io/papers/sigir19_qvae_appendix.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Metric Hybrid Factored Planning in Nonlinear Domains with Constraint Generation.\n \n \n \n \n\n\n \n Say, B.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 16th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-19), Thessaloniki, Greece, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"Metric$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cpaior19,\n  author = {Buser Say and Scott Sanner},\n  year = {2019},\n  title = {Metric Hybrid Factored Planning in Nonlinear Domains with Constraint Generation},\n  booktitle = {Proceedings of the 16th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research ({CPAIOR-19})},\n  address = {Thessaloniki, Greece},\n  url_paper = {https://ssanner.github.io/papers/cpaior19_scipplan.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification.\n \n \n \n \n\n\n \n Wang, Y.; Wu, G.; Bouadjenek, M. R.; Sanner, S.; Su, S.; and Zhang, Z.\n\n\n \n\n\n\n In Proceedings of the SIAM International Conference on Data Mining (SDM-19), Calgary, Canada, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sdm19,\n  author   = {Yakun Wang and Ga Wu and Mohamed Reda Bouadjenek and Scott Sanner and Sen Su and Zhongbao Zhang},\n  title    = {A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification},\n  booktitle = {Proceedings of the SIAM International Conference on Data Mining ({SDM-19})},\n  address   = {Calgary, Canada},\n  year      = {2019},\n  url_paper = {https://ssanner.github.io/papers/sdm19_tempreg.pdf}\n}  \n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Networks for Data Integration in the Absence of Foreign Keys.\n \n \n \n \n\n\n \n Zhang, B.; Sanner, S.; Bouadjenek, M. R.; and Gupta, S.\n\n\n \n\n\n\n IEEE Transactions on Knowledge and Data Engineering (TKDE), 32(4): 803–808. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n \n $\"Bayesian$ appendix\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 24 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:tkde19,\n  author = {Bohan Zhang and Scott Sanner and Mohamed Reda Bouadjenek and Shagun Gupta},\n  title = {Bayesian Networks for Data Integration in the Absence of Foreign Keys},\n  journal = {IEEE Transactions on Knowledge and Data Engineering (TKDE)},\n  year = {2019},\n  volume = {32},\n  number = {4},\n  pages = {803--808},\n  url_paper = {https://ssanner.github.io/papers/tkde19_bnfusion.pdf},\n  url_appendix = {https://ssanner.github.io/papers/tkde19_bnfusion_supp.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Comparison of machine learning models for occupancy prediction in residential buildings using connected thermostat data.\n \n \n \n \n\n\n \n Huchuk, B.; Sanner, S.; and O'Brien, W.\n\n\n \n\n\n\n Building and Environment, 160: 106177. August 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Comparison$ paper\n \n \n \n $\"Comparison$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 13 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:be19,\n\tauthor = {B. Huchuk and S. Sanner and W. O'Brien},\n\ttitle = {Comparison of machine learning models for occupancy prediction in residential buildings using connected thermostat data},\n\tyear = {2019},\n\tjournal = {Building and Environment},\n\tvolume = {160},\n\tpages = {106177},\n\tmonth = {August},\n        url_paper = {https://ssanner.github.io/papers/be19_resoccpred.pdf},\n\turl_url = {https://www.sciencedirect.com/science/article/abs/pii/S0360132319303877}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Evaluation of Machine Learning Algorithms for Predicting Readmission After Acute Myocardial Infarction Using Routinely Collected Clinical Data.\n \n \n \n \n\n\n \n Gupta, S.; Ko, D. T.; Azizi, P.; Bouadjenek, M. R.; Koh, M.; Chong, A.; Austin, P. C.; and Sanner, S.\n\n\n \n\n\n\n Canadian Journal of Cardiology, 36: 878–885. June 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluation$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:cjc19,\n\tauthor = {S. Gupta and D. T. Ko and P. Azizi and M. R. Bouadjenek and M. Koh and A. Chong and P. C. Austin and S. Sanner},\n\ttitle = {Evaluation of Machine Learning Algorithms for Predicting Readmission After Acute Myocardial Infarction Using Routinely Collected Clinical Data},\n\tjournal = {Canadian Journal of Cardiology},\n\tpublisher = {Elsevier},\n\tmonth = {June},\n\tyear = {2019},\n\tvolume = {36},\n\tissue = {6},\n\tpages = {878--885},\n\turl_paper = {http://www.sciencedirect.com/science/article/pii/S0828282X19313583}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2018\n \n \n (10)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach.\n \n \n \n \n\n\n \n Gimelfarb, M.; Sanner, S.; and Lee, C.\n\n\n \n\n\n\n In Proceedings of the 32nd Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-18), Montreal, QC, Canada, 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Reinforcement$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 20 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:nips18,\n  author = {Michael Gimelfarb and Scott Sanner and Chi-Guhn Lee},\n  year = {2018},\n  title = {Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach},\n  booktitle = {Proceedings of the 32nd Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-18})},\n  address = {Montreal, QC, Canada},\n  url_paper = {https://ssanner.github.io/papers/nips18_bmcrs.pdf} \n}  \n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Two-stage Model for Automatic Playlist Continuation at Scale.\n \n \n \n \n\n\n \n Volkovs, M.; Rai, H.; Cheng, Z.; Wu, G.; Lu, Y.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the ACM Recommender Systems Challenge 2018 (RecSys-18), Vancouver, BC, Canada, 2018. \n 1st place in 2018 ACM RecSys Challenge.\n\n\n\n
\n\n\n\n \n \n $\"Two-stage$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:recsys18b,\n  author = {Maksims Volkovs and Himanshu Rai and Zhaoyue Cheng and Ga Wu and Yichao Lu and Scott Sanner},\n  title = {Two-stage Model for Automatic Playlist Continuation at Scale},\n  booktitle = {Proceedings of the ACM Recommender Systems Challenge 2018 ({RecSys-18})},\n  year = {2018},\n  address = {Vancouver, BC, Canada},\n  note = {1st place in 2018 ACM RecSys Challenge.},\n  url_paper = {https://ssanner.github.io/papers/recsys18_challenge.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Aesthetic Features for Personalized Photo Recommendation.\n \n \n \n \n\n\n \n Zhou, Y. Q.; Wu, G.; Sanner, S.; and Manggala, P.\n\n\n \n\n\n\n In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys-18), Vancouver, BC, Canada, 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Aesthetic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:recsys18a,\n  author = {Yu Qing Zhou and Ga Wu and Scott Sanner and Putra Manggala},\n  title = {Aesthetic Features for Personalized Photo Recommendation},\n  year = {2018},\n  booktitle = {Proceedings of the 12th ACM Conference on Recommender Systems ({RecSys-18})},\n  address = {Vancouver, BC, Canada},\n  url_paper = {https://ssanner.github.io/papers/recsys18_aesthetic.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Collaborative Filtering with Behavioral Models.\n \n \n \n \n\n\n \n Sovilj, D.; Sanner, S.; Soh, H.; and Li, H.\n\n\n \n\n\n\n In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (UMAP-18), Singapore, 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Collaborative$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:umap18,\n  author = {Dusan Sovilj and Scott Sanner and Harold Soh and Hanze Li},\n  year = {2018},\n  title = {Collaborative Filtering with Behavioral Models},\n  booktitle = {Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization ({UMAP-18})},\n  address = {Singapore},\n  url_paper = {https://ssanner.github.io/papers/umap18_bbcf.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Symbolic Bucket Elimination for Piecewise Continuous Constrained Optimization.\n \n \n \n \n\n\n \n Ye, Z.; Say, B.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 15th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-18), Delft, Netherlands, 2018. \n Recipient of the Best Student Paper Award.\n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 24 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cpaior18,\n  author = {Zhijiang Ye and Buser Say and Scott Sanner},\n  year = {2018},\n  title = {Symbolic Bucket Elimination for Piecewise Continuous Constrained Optimization},\n  booktitle = {Proceedings of the 15th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research ({CPAIOR-18})},\n  note = {Recipient of the Best Student Paper Award.},\n  address = {Delft, Netherlands},\n  url_paper = {https://ssanner.github.io/papers/cpaior18_sbe.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models.\n \n \n \n \n\n\n \n Say, B.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), Stockholm, Sweden, 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Planning$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 13 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai18a,\n  author = {Buser Say and Scott Sanner},\n  year = {2018},\n  title = {Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models},\n  booktitle = {Proceedings of the 27th International Joint Conference on Artificial Intelligence ({IJCAI-18})},\n  address = {Stockholm, Sweden},\n  url_paper = {https://ssanner.github.io/papers/ijcai18_bnnplan.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Efficient Symbolic Integration for Probabilistic Inference.\n \n \n \n \n\n\n \n Kolb, S.; Mladenov, M.; Sanner, S.; Belle, V.; and Kersting, K.\n\n\n \n\n\n\n In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), Stockholm, Sweden, 2018. \n \n\n\n\n
\n\n\n\n \n \n $\"Efficient$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai18b,\n  author = {Samuel Kolb and Martin Mladenov and Scott Sanner and Vaishak Belle and Kristian Kersting},\n  year = {2018},\n  title = {Efficient Symbolic Integration for Probabilistic Inference},\n  booktitle = {Proceedings of the 27th International Joint Conference on Artificial Intelligence ({IJCAI-18})},\n  address = {Stockholm, Sweden},\n  url_paper = {https://ssanner.github.io/papers/ijcai18_symint.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Longitudinal Study of Thermostat Behaviors based on Climate, Seasonal, and Energy Price Considerations using Connected Thermostat Data.\n \n \n \n \n\n\n \n Huchuk, B.; O'Brien, W.; and Sanner, S.\n\n\n \n\n\n\n Building and Environment, 139: 199–210. July 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n \n $\"A$ url\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:be18,\n\tauthor = {B. Huchuk and W. O'Brien and S. Sanner},\n\ttitle = {A Longitudinal Study of Thermostat Behaviors based on Climate, Seasonal, and Energy Price Considerations using Connected Thermostat Data},\n\tyear = {2018},\n\tjournal = {Building and Environment},\n\tvolume = {139},\n\tmonth = {July},\n\tpages = {199--210},\n        url_paper = {https://ssanner.github.io/papers/be18_reslongstudy.pdf},\n        url_url = {https://www.sciencedirect.com/science/article/pii/S0360132318302634}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Measuring and Mitigating the Costs of Attentional Switches in Active Network Monitoring for Cybersecurity.\n \n \n \n \n\n\n \n Kortschot, S. W.; Sovilj, D.; Jamieson, G. A.; Sanner, S.; Carrasco, C.; and Soh, H.\n\n\n \n\n\n\n Human Factors. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Measuring$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:hf18,\n\tauthor = {S. W. Kortschot and D. Sovilj and G. A. Jamieson and S. Sanner and C. Carrasco and H. Soh},\n\ttitle = {Measuring and Mitigating the Costs of Attentional Switches in Active Network Monitoring for Cybersecurity},\n\tyear = {2018},\n\tjournal = {Human Factors},\n\turl_paper = {http://journals.sagepub.com/doi/10.1177/0018720818784107}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Deep Learning with Microfluidics for Biotechnology.\n \n \n \n \n\n\n \n Riordon, J.; Sovilj, D.; Sanner, S.; Sinton, D.; and Young, E.\n\n\n \n\n\n\n Trends in Biotechnology. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Deep$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:tb18,\n  author = {Jason Riordon and Dusan Sovilj and Scott Sanner and David Sinton and {Edmond W.K.} Young},\n  title = {Deep Learning with Microfluidics for Biotechnology},\n  year = {2018},\n  journal = {Trends in Biotechnology},\n  url_paper = {https://doi.org/10.1016/j.tibtech.2018.08.005}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2017\n \n \n (11)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Scalable Planning with Tensorflow for Hybrid Nonlinear Domains.\n \n \n \n \n\n\n \n Wu, G.; Say, B.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 31st Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-17), Long Beach, CA, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"Scalable$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 35 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:nips17,\n  author = {Ga Wu and Buser Say and Scott Sanner},\n  year = {2017},\n  title = {Scalable Planning with Tensorflow for Hybrid Nonlinear Domains},\n  booktitle = {Proceedings of the 31st Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-17})},\n  address = {Long Beach, CA},\n  url_paper = {https://ssanner.github.io/papers/nips17_tfplan.pdf}\n}  \n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming.\n \n \n \n \n\n\n \n Say, B.; Wu, G.; Zhou, Y. I.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne, Australia, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"Nonlinear$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 20 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai17,\n  author = {Buser Say and Ga Wu and Yuqing Ivan Zhou and Scott Sanner},\n  year = {2017},\n  title = {Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming},\n  booktitle = {Proceedings of the 26th International Joint Conference on Artificial Intelligence ({IJCAI-17})},\n  address = {Melbourne, Australia},\n  url_paper = {https://ssanner.github.io/papers/ijcai17_hdmilp.pdf}\n}  \n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Longitudinal Study of Topic Classification on Twitter.\n \n \n \n \n\n\n \n Iman, Z.; Sanner, S.; Bouadjenek, M. R.; and Xie, L.\n\n\n \n\n\n\n In Proceedings of the 11th International AAAI Conference on Web and Social Media (ICWSM-17), Montreal, Canada, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 9 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icwsm17,\n  author = "Zahra Iman and Scott Sanner and Mohamed Reda Bouadjenek and Lexing Xie",\n  year = "2017",\n  title = "A Longitudinal Study of Topic Classification on Twitter",\n  booktitle = "Proceedings of the 11th International AAAI Conference on Web and Social Media ({ICWSM-17})",\n  address = {Montreal, Canada},\n  url_paper = {https://ssanner.github.io/papers/icwsm17_tclass.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Analytic Decision Analysis via Symbolic Dynamic Programming for Parameterized Hybrid MDPs.\n \n \n \n \n\n\n \n Kinathil, S.; Soh, H.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 27th Conference on Automated Planning and Scheduling (ICAPS-17), Pittsburgh, PA, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"Analytic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icaps17,\n  author = "Shamin Kinathil and Harold Soh and Scott Sanner",\n  year = "2017",\n  title = "Analytic Decision Analysis via Symbolic Dynamic Programming for Parameterized Hybrid MDPs",\n  booktitle = "Proceedings of the 27th Conference on Automated Planning and Scheduling ({ICAPS-17})",\n  address = {Pittsburgh, PA},\n  url_paper = {https://ssanner.github.io/papers/icaps17_phmdp.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity.\n \n \n \n \n\n\n \n Rizoiu, M.; Xie, L.; Sanner, S.; Cebrian, M.; Yu, H.; and Van Hentenryck, P.\n\n\n \n\n\n\n In Proceedings of the 26th International Conference on the World Wide Web (WWW-17), Perth, Australia, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"Expecting$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:www17,\n  author = {Marian-Andrei Rizoiu and Lexing Xie and Scott Sanner and Manuel Cebrian and Honglin Yu and Pascal {Van Hentenryck}},\n  title = {Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity},\n  year = {2017},\n  booktitle = {Proceedings of the 26th International Conference on the World Wide Web ({WWW-17})},\n  address = {Perth, Australia},\n  url_paper = {https://ssanner.github.io/papers/www17_hip.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Deep Sequential Recommendation for Personalized Adaptive User Interfaces.\n \n \n \n \n\n\n \n Soh, H.; Sanner, S.; White, M.; and Jamieson, G.\n\n\n \n\n\n\n In Proceedings of the 22nd ACM International Conference on Intelligent User Interfaces (IUI-17), Limassol, Cyprus, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"Deep$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:iui17,\n  author = {Harold Soh and Scott Sanner and Madeleine White and Greg Jamieson},\n  title = {Deep Sequential Recommendation for Personalized Adaptive User Interfaces},\n  year = {2017},\n  booktitle = {Proceedings of the 22nd {ACM} International Conference on Intelligent User Interfaces {(IUI-17)}},\n  address = {Limassol, Cyprus},\n  url_paper = {https://ssanner.github.io/papers/iui17_deeprec.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Hindsight Optimization for Hybrid State and Action MDPs.\n \n \n \n \n\n\n \n Raghavan, A.; Sanner, S.; Tadepalli, P.; Fern, A.; and Khardon, R.\n\n\n \n\n\n\n In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, USA, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"Hindsight$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 24 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai17a,\n  author = {Aswin Raghavan and Scott Sanner and Prasad Tadepalli and Alan Fern and Roni Khardon},\n  title = {Hindsight Optimization for Hybrid State and Action MDPs},\n  year = {2017},\n  booktitle = {Proceedings of the 31st {AAAI} Conference on Artificial Intelligence ({AAAI-17})},\n  address = {San Francisco, USA},\n  url_paper = {https://ssanner.github.io/papers/aaai17_hsahop.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Low-rank Linear Cold-Start Recommendation from Social Data.\n \n \n \n \n\n\n \n Sedhain, S.; Menon, A.; Sanner, S.; Xie, L.; and Braziunas, D.\n\n\n \n\n\n\n In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, USA, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"Low-rank$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 11 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai17b,\n  author = {Suvash Sedhain and Aditya Menon and Scott Sanner and Lexing Xie and Darius Braziunas},\n  title = {Low-rank Linear Cold-Start Recommendation from Social Data},\n  year = {2017},\n  booktitle = {Proceedings of the 31st {AAAI} Conference on Artificial Intelligence ({AAAI-17})},\n  address = {San Francisco, USA},\n  url_paper = {https://ssanner.github.io/papers/aaai17_loco.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Non-Markovian Rewards Expressed in LTL: Guiding Search Via Reward Shaping.\n \n \n \n \n\n\n \n Camacho, A.; Chen, O.; Sanner, S.; and McIlraith, S. A.\n\n\n \n\n\n\n In Proceedings of the Tenth International Symposium on Combinatorial Search (SoCS-17), pages 159–160, 2017. \n \n\n\n\n
\n\n\n\n \n \n $\"Non-Markovian$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:socs17,\n  author    = {Alberto Camacho and\n               Oscar Chen and\n               Scott Sanner and\n               Sheila A. McIlraith},\n  title     = {Non-Markovian Rewards Expressed in {LTL:} Guiding Search Via Reward Shaping},\n  booktitle = {Proceedings of the Tenth International Symposium on Combinatorial Search ({SoCS-17})},\n  url_paper = {http://www.cs.toronto.edu/~sheila/publications/cam-etal-socs17.pdf},\n  pages     = {159--160},\n  year      = {2017}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Decision-Making with Non-Markovian Rewards: From LTL to automata-based reward shaping.\n \n \n \n \n\n\n \n Camacho, A.; Chen, O.; Sanner, S.; and McIlraith, S. A.\n\n\n \n\n\n\n In Proceedings of the Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM-17), pages 279-283, 2017. \n See also University of Toronto Technical Report CSRG-632\n\n\n\n
\n\n\n\n \n \n $\"Decision-Making$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:rldm17,\n  author    = {Alberto Camacho and\n               Oscar Chen and\n               Scott Sanner and\n               Sheila A. McIlraith},\n  title     = {Decision-Making with Non-Markovian Rewards: From {LTL} to automata-based reward shaping},\n  booktitle = {Proceedings of the Multi-disciplinary Conference on Reinforcement Learning and Decision Making ({RLDM-17})},\n  pages={279-283},\n  url_paper = {http://www.cs.toronto.edu/~sheila/publications/cam-etal-rldm17.pdf},\n  year      = {2017},\n  note = {See also University of Toronto Technical Report CSRG-632}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Decision-Making with Non-Markovian Rewards: Guiding search via automata-based reward shaping.\n \n \n \n \n\n\n \n Camacho, A.; Chen, O.; Sanner, S.; and McIlraith, S. A.\n\n\n \n\n\n\n Technical Report CSRG-632, Department of Computer Science, University of Toronto, June 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Decision-Making$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 14 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@techreport{sanner:techreport17,\n  title = {Decision-Making with Non-Markovian Rewards: Guiding search via automata-based reward shaping},\n  author    = {Alberto Camacho and\n               Oscar Chen and\n               Scott Sanner and\n               Sheila A. McIlraith},\n  url_paper = {ftp://ftp.cs.toronto.edu/csrg-technical-reports/632/cam-che-san-mci-tr2017.pdf},\n  year = {2017},\n  month = {June},\n  institution = {Department of Computer Science, University of Toronto},\n  number = {CSRG-632}\n}\t\t\t\t\t\t\t   \n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2016\n \n \n (7)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling, ICAPS 2016, London, UK, June 12-17, 2016.\n \n \n \n\n\n \n Coles, A. J.; Coles, A.; Edelkamp, S.; Magazzeni, D.; and Sanner, S.,\n editors.\n \n\n\n \n\n\n\n AAAI Press. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@proceedings{sanner:icaps16,\n  editor = {Amanda Jane Coles and Andrew Coles and Stefan Edelkamp and Daniele Magazzeni and Scott Sanner},\n  title  = {Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling, {{ICAPS}} 2016, London, UK, June 12-17, 2016},\n  publisher = "{AAAI} Press",\n  year      = "2016"\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Real-time Dynamic Programming for Markov Decision Processes with Imprecise Probabilities.\n \n \n \n \n\n\n \n Delgado, K. V.; de Barros, L. N.; Dias, D. B.; and Sanner, S.\n\n\n \n\n\n\n Artificial Intelligence Journal (AIJ), 230: 192–223. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Real-time$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:aij16,\n  author = {K. V. Delgado and L. N. de Barros and D. B. Dias and S. Sanner},\n  title = {Real-time Dynamic Programming for Markov Decision Processes with Imprecise Probabilities},\n  year = {2016},\n  journal = "Artificial Intelligence Journal ({AIJ})",\n  volume = "230",\n  pages = "192--223",\n  url_paper = {http://www.sciencedirect.com/science/article/pii/S0004370215001411}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Non-homogenous Time Mixed Integer LP Formulation for Traffic Signal Control.\n \n \n \n \n\n\n \n Guilliard, I.; Sanner, S.; Trevizan, F.; and Williams, B.\n\n\n \n\n\n\n Transport Research Record (TRR): Journal of the Transport Research Board, 2525. 2016.\n Recipient of the Kikuchi-Karlaftis Best Paper Award.\n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:trr16,\n  author = {I. Guilliard and S. Sanner and F. Trevizan and B. Williams},\n  title = {A Non-homogenous Time Mixed Integer LP Formulation for Traffic Signal Control},\n  year = {2016},\n  volume = {2525},\n  note = {Recipient of the Kikuchi-Karlaftis Best Paper Award.},\n  journal = {Transport Research Record ({TRR}): Journal of the Transport Research Board},\n  url_paper = {https://ssanner.github.io/papers/anu/TRR_qtm_paper.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Practical Linear Models for Large-Scale One-Class Collaborative Filtering.\n \n \n \n \n\n\n \n Sedhain, S.; Bui, H.; Kawale, J.; Vlassis, N.; Kveton, B.; Menon, A.; Bui, T.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), New York, USA, 2016. \n \n\n\n\n
\n\n\n\n \n \n $\"Practical$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 18 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai16a,\n  author = {S. Sedhain and H. Bui and J. Kawale and N. Vlassis and B. Kveton and A. Menon and T. Bui and S. Sanner},\n  year = {2016},\n  title = {Practical Linear Models for Large-Scale One-Class Collaborative Filtering},\n  booktitle = {Proceedings of the 25th International Joint Conference on Artificial Intelligence ({IJCAI-16})},\n  address = {New York, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/ijcai16_proj_lrec.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Symbolic Closed-form Solution to Sequential Market Making with Inventory.\n \n \n \n \n\n\n \n Kinathil, S.; Sanner, S.; Das, S.; and Della-Penna, N.\n\n\n \n\n\n\n In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), New York, USA, 2016. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai16b,\n  author = {S. Kinathil and S. Sanner and S. Das and N. Della-Penna},\n  year = {2016},\n  title = {A Symbolic Closed-form Solution to Sequential Market Making with Inventory},\n  booktitle = {Proceedings of the 25th International Joint Conference on Artificial Intelligence ({IJCAI-16})},\n  address = {New York, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/ijcai16_mm.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Closed-form Gibbs Sampling for Graphical Models with Algebraic Constraints.\n \n \n \n \n\n\n \n Afshar, H.; Sanner, S.; and Webers, C.\n\n\n \n\n\n\n In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, USA, 2016. \n \n\n\n\n
\n\n\n\n \n \n $\"Closed-form$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 10 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai16a,\n  author = {H. Afshar and S. Sanner and C. Webers},\n  title = {Closed-form Gibbs Sampling for Graphical Models with Algebraic Constraints},\n  year = {2016},\n  booktitle = {Proceedings of the 30th {AAAI} Conference on Artificial Intelligence ({AAAI-16})},\n  address = {Phoenix, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/aaai16_sgibbs.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n On the Effectiveness of Linear Models for One-Class Collaborative Filtering.\n \n \n \n \n\n\n \n Sedhain, S.; Menon, A.; Sanner, S.; and Braziunas, D.\n\n\n \n\n\n\n In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, USA, 2016. \n \n\n\n\n
\n\n\n\n \n \n $\"On$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai16b,\n  author = {S. Sedhain and A. Menon and S. Sanner and D. Braziunas},\n  title = {On the Effectiveness of Linear Models for One-Class Collaborative Filtering},\n  year = {2016},\n  booktitle = {Proceedings of the 30th {AAAI} Conference on Artificial Intelligence ({AAAI-16})},\n  address = {Phoenix, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/aaai16_lrec.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2015\n \n \n (10)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n The 2014 International Planning Competition: Progress and Trends.\n \n \n \n \n\n\n \n Vallati, M.; Chrpa, L.; Grzes, M.; McCluskey, T. L.; Roberts, M.; and Sanner, S.\n\n\n \n\n\n\n Artificial Intelligence Magazine (AI Magazine), 36(3): 90–98. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:aimag15,\n  author     = {M. Vallati and L. Chrpa and M. Grzes and T. L. McCluskey and M. Roberts and S. Sanner},\n  title      = {The 2014 International Planning Competition: Progress and Trends}, \n  journal    = {Artificial Intelligence Magazine ({AI Magazine})},\n  year       = {2015},\n  volume={36},\n  number={3},\n  pages={90--98},\n  url_paper = {https://ssanner.github.io/papers/anu/aimag15_ipc.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n AutoRec: Autoencoders Meet Collaborative Filtering.\n \n \n \n \n\n\n \n Sedhain, S.; Menon, A.; Sanner, S.; and Xie, L.\n\n\n \n\n\n\n In Proceedings of the 24th International Conference on the World Wide Web (WWW-15), Florence, Italy, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"AutoRec:$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:www15,\n  author    = {S. Sedhain and A. Menon and S. Sanner and L. Xie},\n  title     = {AutoRec: Autoencoders Meet Collaborative Filtering},\n  booktitle = {Proceedings of the 24th International Conference on the World Wide Web {(WWW-15)}},\n  address   = {Florence, Italy},\n  year      = {2015},\n  url_paper = {https://ssanner.github.io/papers/anu/www15.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The Lifecyle of a Youtube Video: Phases, Content and Popularity.\n \n \n \n \n\n\n \n Yu, H.; Xie, L.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 9th International Conference on Web and Social Media (ICWSM-15), Oxford, UK, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"The$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icwsm15,\n  author    = {H. Yu and L. Xie and S. Sanner},\n  title     = {The Lifecyle of a Youtube Video: Phases, Content and Popularity},\n  booktitle = {Proceedings of the 9th International Conference on Web and Social Media {(ICWSM-15)}},\n  address   = {Oxford, UK},\n  year      = {2015},\n  url_paper = {https://ssanner.github.io/papers/anu/icwsm15.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Linear-time Gibbs Sampling in Piecewise Graphical Models.\n \n \n \n \n\n\n \n Afshar, H.; Sanner, S.; and Abbasnejad, E.\n\n\n \n\n\n\n In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"Linear-time$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai15a,\n  author = {H. Afshar and S. Sanner and E. Abbasnejad},\n  title = {Linear-time {Gibbs} Sampling in Piecewise Graphical Models},\n  year = {2015},\n  booktitle = {Proceedings of the 29th {AAAI} Conference on Artificial Intelligence ({AAAI-15})},\n  address = {Austin, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/aaai15_fb.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Loss-calibrated Monte Carlo Action Selection.\n \n \n \n \n\n\n \n Abbasnejad, E.; Domke, J.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"Loss-calibrated$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai15b,\n  author = {E. Abbasnejad and J. Domke and S. Sanner},\n  title = {Loss-calibrated {Monte Carlo} Action Selection},\n  year = {2015},\n  booktitle = {Proceedings of the 29th {AAAI} Conference on Artificial Intelligence ({AAAI-15})},\n  address = {Austin, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/aaai15_mcas.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Real-time Symbolic Dynamic Programming for Hybrid MDPs.\n \n \n \n \n\n\n \n Vianna, L. G. R.; de Barros, L. N.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"Real-time$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai15c,\n  author = {L. G. Rocha Vianna and L. N. de Barros and S. Sanner},\n  title = {Real-time Symbolic Dynamic Programming for Hybrid {MDPs}},\n  year = {2015},\n  booktitle = {Proceedings of the 29th {AAAI} Conference on Artificial Intelligence ({AAAI-15})},\n  address = {Austin, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/aaai15_rtsdp.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Model Averaging Naive Bayes: Averaging over an Exponential Number of Feature Models in Linear Time.\n \n \n \n \n\n\n \n Wu, G.; Sanner, S.; and Oliveira, R. F.\n\n\n \n\n\n\n In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 28 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai15d,\n  author = {G. Wu and S. Sanner and Rodrigo F.S.C. Oliveira},\n  title = {Bayesian Model Averaging Naive {Bayes}: Averaging over an Exponential Number of Feature Models in Linear Time},\n  year = {2015},\n  booktitle = {Proceedings of the 29th {AAAI} Conference on Artificial Intelligence ({AAAI-15})},\n  address = {Austin, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/aaai15_bmanb.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n On Term Selection Techniques for Patent Prior Art Search.\n \n \n \n \n\n\n \n Far, M. G.; Sanner, S.; Bouadjenek, M. R.; Ferraro, G.; and Hawking, D.\n\n\n \n\n\n\n In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-15), pages 803–806, Santiago, Chile, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"On$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir15,\n  author    = {M. Golestan Far and S. Sanner and M. R. Bouadjenek and G. Ferraro and D. Hawking},\n  title     = {On Term Selection Techniques for Patent Prior Art Search},\n  booktitle = {Proceedings of the 38th International {ACM} {SIGIR} Conference on Research and Development in Information Retrieval {(SIGIR-15)}},\n  address   = {Santiago, Chile},\n  pages     = {803--806},\n  year      = {2015},\n  url_paper = {https://ssanner.github.io/papers/anu/sigir15_patents.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Study of Query Reformulation for Patent Prior Art Search with Partial Patent Applications.\n \n \n \n \n\n\n \n Bouadjenek, M. R.; Sanner, S.; and Ferraro, G.\n\n\n \n\n\n\n In Proceedings of the 15th International Conference on Artificial Intelligence and Law (ICAIL-15), pages 23–32, San Diego, USA, 2015. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icail15,\n  author    = {M. R. Bouadjenek and S. Sanner and G. Ferraro},\n  title     = {A Study of Query Reformulation for Patent Prior Art Search with Partial Patent Applications},\n  booktitle = {Proceedings of the 15th International Conference on Artificial Intelligence and Law {(ICAIL-15)}},\n  address   = {San Diego, USA},\n  pages     = {23--32},\n  year      = {2015},\n  url_paper = {https://ssanner.github.io/papers/anu/icail15.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Context-Aware Detection of Sneaky Vandalism on Wikipedia Across Multiple Languages.\n \n \n \n \n\n\n \n Tran, K.; Christen, P.; Sanner, S.; and Xie, L.\n\n\n \n\n\n\n In Advances in Knowledge Discovery and Data Mining - 19th Pacific-Asia Conference (PAKDD-15), pages 380–391, Ho Chi Minh City, Vietnam, 2015. \n Recipient of the Best Student Paper Award.\n\n\n\n
\n\n\n\n \n \n $\"Context-Aware$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:pakdd15,\n  author    = {K.{-}N. Tran and P. Christen and S. Sanner and L. Xie},\n  title     = {Context-Aware Detection of Sneaky Vandalism on Wikipedia Across Multiple Languages},\n  booktitle = {Advances in Knowledge Discovery and Data Mining - 19th Pacific-Asia Conference {(PAKDD-15)}},\n  address   = {Ho Chi Minh City, Vietnam},\n  note = {Recipient of the Best Student Paper Award.},\n  pages     = {380--391},\n  year      = {2015},\n  url_paper = {https://ssanner.github.io/papers/anu/pakdd15.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2014\n \n \n (5)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Social Collaborative Filtering for Cold-start Recommendations.\n \n \n \n \n\n\n \n Sedhain, S.; Sanner, S.; Braziunas, D.; Xie, L.; and Christensen, J.\n\n\n \n\n\n\n In Proceedings of the 8th ACM Conference on Recommender Systems (RecSys-14), Foster City, USA, 2014. \n \n\n\n\n
\n\n\n\n \n \n $\"Social$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:recsys14,\n  author = {S. Sedhain and S. Sanner and D. Braziunas and L. Xie and J. Christensen},\n  year = {2014},\n  title = {Social Collaborative Filtering for Cold-start Recommendations},\n  booktitle = {Proceedings of the 8th {ACM} Conference on Recommender Systems ({RecSys-14})},\n  address = {Foster City, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/recsys14.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Twitter-driven Youtube Views: Beyond Individual Influencers.\n \n \n \n \n\n\n \n Yu, H.; Xie, L.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 22nd ACM International Conference on Multimedia (ACM MM-14), Orlando, USA, 2014. \n \n\n\n\n
\n\n\n\n \n \n $\"Twitter-driven$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:acmmm14,\n  author = {H. Yu and L. Xie and S. Sanner},\n  year = {2014},\n  title = {Twitter-driven Youtube Views: Beyond Individual Influencers},\n  booktitle = {Proceedings of the 22nd {ACM} International Conference on Multimedia ({ACM MM-14})},\n  address = {Orlando, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/acmmm14.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Sequential Bayesian Optimisation for Spatial-Temporal Monitoring.\n \n \n \n \n\n\n \n Marchant, R.; Ramos, F.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI-14), Quebec City, Canada, 2014. \n \n\n\n\n
\n\n\n\n \n \n $\"Sequential$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai14a,\n  author = {R. Marchant and F. Ramos and S. Sanner},\n  year = {2014}, \n  title = {Sequential Bayesian Optimisation for Spatial-Temporal Monitoring},\n  booktitle = {Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence ({UAI-14})},\n  address = {Quebec City, Canada},\n  url_paper = {https://ssanner.github.io/papers/anu/uai14sbo.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Closed-form Solutions to a Subclass of Continuous Stochastic Games via Symbolic Dynamic Programming.\n \n \n \n \n\n\n \n Kinathil, S.; Sanner, S.; and Penna, N. D.\n\n\n \n\n\n\n In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI-14), Quebec City, Canada, 2014. \n \n\n\n\n
\n\n\n\n \n \n $\"Closed-form$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai14b,\n  author = {S. Kinathil and S. Sanner and N. Della Penna},\n  year = {2014}, \n  title = {Closed-form Solutions to a Subclass of Continuous Stochastic Games via Symbolic Dynamic Programming},\n  booktitle = {Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence ({UAI-14})},\n  address = {Quebec City, Canada},\n  url_paper = {https://ssanner.github.io/papers/anu/uai14czerosum.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Preference Learning (Dagstuhl Seminar 14101).\n \n \n \n \n\n\n \n Fürnkranz, J.; Hüllermeier, E.; Rudin, C.; Slowinski, R.; and Sanner, S.\n\n\n \n\n\n\n Dagstuhl Reports, 4(3): 1–27. 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Preference$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:dagstuhl14,\n  author =\t{J. F{\\"u}rnkranz and E. H{\\"u}llermeier and C. Rudin and R. Slowinski and S. Sanner},\n  title =\t{{Preference Learning (Dagstuhl Seminar 14101)}},\n  pages =\t{1--27},\n  journal =\t{{Dagstuhl Reports}},\n  ISSN =\t{2192-5283},\n  year =\t{2014},\n  volume =\t{4},\n  number =\t{3},\n  editor =\t{Johannes F{\\"u}rnkranz and Eyke H{\\"u}llermeier and Cynthia Rudin and Roman Slowinski and Scott Sanner},\n  publisher =\t{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},\n  address =\t{Dagstuhl, Germany},\n  URL =\t\t{http://drops.dagstuhl.de/opus/volltexte/2014/4550/pdf/dagrep_v004_i003_p001_s14101.pdf},\n  doi =\t\t{http://dx.doi.org/10.4230/DagRep.4.3.1}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2013\n \n \n (6)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPs.\n \n \n \n \n\n\n \n Vianna, L. G. R.; Sanner, S.; and de Barros, L. N.\n\n\n \n\n\n\n In Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (UAI-13), Bellevue, USA, 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Bounded$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 9 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai13,\n  author = {L. G. Rocha Vianna and S. Sanner and L. N. de Barros},\n  year = {2013}, \n  title = {Bounded Approximate Symbolic Dynamic Programming for Hybrid {MDP}s},\n  booktitle = {Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence ({UAI-13})},\n  address = {Bellevue, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/uai13.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Algorithms for Direct 0-1 Loss Optimization in Binary Classification.\n \n \n \n \n\n\n \n Nguyen, T.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 30th International Conference on Machine Learning (ICML-13), Atlanta, USA, 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Algorithms$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icml13,\n  author = {T. Nguyen and S. Sanner},\n  title = {Algorithms for Direct 0-1 Loss Optimization in Binary Classification},\n  booktitle = {Proceedings of the 30th International Conference on Machine Learning ({ICML-13})},\n  address = {Atlanta, USA},\n  year = {2013},\n  url_paper = {https://ssanner.github.io/papers/anu/icml13.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Improving LDA Topic Models for Microblogs via Automatic Tweet Labeling and Pooling.\n \n \n \n \n\n\n \n Mehrotra, R.; Sanner, S.; Buntine, W.; and Xie, L.\n\n\n \n\n\n\n In Proceedings of the 36th Annual ACM SIG Information Retrieval Conference (SIGIR-13), Dublin, Ireland, 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Improving$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 14 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir13,\n  author = {R. Mehrotra and S. Sanner and W. Buntine and L. Xie},\n  title = {Improving {LDA} Topic Models for Microblogs via Automatic Tweet Labeling and Pooling},\n  booktitle = {Proceedings of the 36th Annual ACM SIG Information Retrieval Conference ({SIGIR-13})},\n  address = {Dublin, Ireland},\n  year = {2013},\n  url_paper = {https://ssanner.github.io/papers/anu/sigir13.pdf}\n} \n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Learning Community-based Preferences via Dirichlet Process Mixtures of Gaussian Processes.\n \n \n \n \n\n\n \n Abbasnejad, E.; Sanner, S.; Bonilla, E. V.; and Poupart, P.\n\n\n \n\n\n\n In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-13), Beijing, China, 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai13a,\n  author = {E. Abbasnejad and S. Sanner and E. V. Bonilla and P. Poupart}, \n  title = {Learning Community-based Preferences via Dirichlet Process Mixtures of Gaussian Processes}, \n  booktitle = {Proceedings of the 23rd International Joint Conference on Artificial Intelligence ({IJCAI-13})}, \n  address = {Beijing, China},\n  year = {2013},\n  url_paper = {https://ssanner.github.io/papers/anu/mogp.pdf} \n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Robust Optimization for Hybrid MDPs with State-dependent Noise.\n \n \n \n \n\n\n \n Zamani, Z.; Sanner, S.; Delgado, K. V.; and de Barros , L. N.\n\n\n \n\n\n\n In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-13), Beijing, China, 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Robust$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai13b,\n  author = {Z. Zamani and S. Sanner and K. V. Delgado and L. Nunes {de Barros}},\n  title = {Robust Optimization for Hybrid {MDPs} with State-dependent Noise}, \n  booktitle = {Proceedings of the 23rd International Joint Conference on Artificial Intelligence ({IJCAI-13})}, \n  address = {Beijing, China},\n  year = {2013},\n  url_paper = {https://ssanner.github.io/papers/anu/hybnoise.pdf} \n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Social Affinity Filtering: Recommendation through Fine-grained Analysis of User Interactions and Activities.\n \n \n \n \n\n\n \n Sedhain, S.; Sanner, S.; Xie, L.; Kidd, R.; Tran, K.; and Christen, P.\n\n\n \n\n\n\n In Proceedings of the ACM Conference on Online Social Networks (COSN-13), Boston, USA, 2013. \n \n\n\n\n
\n\n\n\n \n \n $\"Social$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cosn13,\n  author = {S. Sedhain and S. Sanner and L. Xie and R. Kidd and K.-N. Tran and P. Christen},\n  title = {Social Affinity Filtering: Recommendation through Fine-grained Analysis of User Interactions and Activities},\n  booktitle = {Proceedings of the ACM Conference on Online Social Networks ({COSN-13})},\n  address = {Boston, USA},\n  year= {2013},\n  url_paper = {https://ssanner.github.io/papers/anu/cosn13.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2012\n \n \n (8)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Symbolic Dynamic Programming for Continuous State and Observation POMDPs.\n \n \n \n \n\n\n \n Zamani, Z.; Sanner, S.; Poupart, P.; and Kersting, K.\n\n\n \n\n\n\n In Proceedings of the 26th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-12), Lake Tahoe, Nevada, 2012. \n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:nips12,\n  author = {Z. Zamani and S. Sanner and P. Poupart and K. Kersting},\n  year = {2012},\n  title = {Symbolic Dynamic Programming for Continuous State and Observation POMDPs},\n  booktitle = {Proceedings of the 26th Annual Conference on Advances in Neural Information Processing Systems ({NeurIPS-12})},\n  address = {Lake Tahoe, Nevada},\n  url_paper = {https://ssanner.github.io/papers/anu/nips12.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Score-based Bayesian Skill Learning.\n \n \n \n \n\n\n \n Guo, S.; Sanner, S.; Graepel, T.; and Buntine, W.\n\n\n \n\n\n\n In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-12), Bristol, UK, 2012. \n \n\n\n\n
\n\n\n\n \n \n $\"Score-based$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ecml12,\n  author = {S. Guo and S. Sanner and T. Graepel and W. Buntine},\n  year = {2012},\n  title = {Score-based Bayesian Skill Learning},\n  booktitle = {Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases ({ECML/PKDD-12})}, \n  address = {Bristol, UK},\n  url_paper = {https://ssanner.github.io/papers/anu/sbsl_ecml2012.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Symbolic Variable Elimination for Discrete and Continuous Graphical Models.\n \n \n \n \n\n\n \n Sanner, S.; and Abbasnejad, E.\n\n\n \n\n\n\n In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, 2012. \n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai12a,\n  author = {S. Sanner and E. Abbasnejad},\n  year = {2012},\n  title = {Symbolic Variable Elimination for Discrete and Continuous Graphical Models},\n  booktitle = {Proceedings of the 26th AAAI Conference on Artificial Intelligence ({AAAI-12})},\n  address = {Toronto, Canada},\n  url_paper = {https://ssanner.github.io/papers/anu/aaai12_sve.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Symbolic Dynamic Programming for Continuous State and Action MDPs.\n \n \n \n \n\n\n \n Zamani, Z.; Sanner, S.; and Fang, C.\n\n\n \n\n\n\n In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, 2012. \n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 15 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai12b,\n  author = {Z. Zamani and S. Sanner and C. Fang},\n  year = {2012},\n  title = {Symbolic Dynamic Programming for Continuous State and Action MDPs},\n  booktitle = {Proceedings of the 26th AAAI Conference on Artificial Intelligence ({AAAI-12})},\n  address = {Toronto, Canada},\n  url_paper = {https://ssanner.github.io/papers/anu/aaai12_sdp.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off.\n \n \n \n \n\n\n \n Lim, K.; Sanner, S.; and Guo, S.\n\n\n \n\n\n\n In Proceedings of the 35th Annual ACM SIG Information Retrieval Conference (SIGIR-12), Portland, USA, 2012. \n \n\n\n\n
\n\n\n\n \n \n $\"On$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 10 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:sigir12,\n  author = {K.-W. Lim and S. Sanner and S. Guo},\n  year = {2012},\n  title = {On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off},\n  booktitle = {Proceedings of the 35th Annual ACM SIG Information Retrieval Conference ({SIGIR-12})},\n  address = {Portland, USA},\n  url_paper = {https://ssanner.github.io/papers/anu/sigir12.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n New Objectives for Social Collaborative Filtering.\n \n \n \n \n\n\n \n Noel, J.; Sanner, S.; Tran, K.; Christen, P.; Xie, L.; Bonilla, E.; Abbasnejad, E.; and Penna, N. D.\n\n\n \n\n\n\n In Proceedings of the 21st International Conference on the World Wide Web (WWW-12), Lyon, France, 2012. \n \n\n\n\n
\n\n\n\n \n \n $\"New$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 47 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:www12,\n  author = {J. Noel and S. Sanner and K-N. Tran and P. Christen and L. Xie and E. Bonilla and E. Abbasnejad and N. Della Penna},\n  year = {2012},\n  title = {New Objectives for Social Collaborative Filtering},\n  booktitle = {Proceedings of the 21st International Conference on the World Wide Web ({WWW-12})},\n  address = {Lyon, France},\n  url_paper = {https://ssanner.github.io/papers/anu/www12.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Proceedings of the 9th European Workshop on Reinforcement Learning (EWRL) 2011, Athens, Greece, September 9-11, 2011.\n \n \n \n \n\n\n \n Sanner, S.; and Hutter, M.,\n editors.\n \n\n\n \n\n\n\n Volume 7188, of Lecture Notes in Computer Science.Springer. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Proceedings$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@proceedings{sanner:ewrl12,\n  editor = {S. Sanner and M. Hutter},\n  title = {Proceedings of the 9th European Workshop on Reinforcement Learning\n           ({EWRL}) 2011, Athens, Greece, September 9-11, 2011},\n  booktitle = {{EWRL}},\n  publisher = {Springer},\n  series = {Lecture Notes in Computer Science},\n  volume = {7188},\n  year = {2012},\n  url_paper = {https://ssanner.github.io/papers/anu/ewrl11_preface.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A Survey of the Seventh International Planning Competition.\n \n \n \n \n\n\n \n Coles, A.; Coles, A.; Olaya, A. G.; Jiménez, S.; López, C. L.; Sanner, S.; and Yoon, S.\n\n\n \n\n\n\n Artificial Intelligence Magazine (AI Magazine), 33(1): 83–88. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:aimag12,\n  title={A Survey of the Seventh International Planning Competition}, \n  journal={Artificial Intelligence Magazine ({AI Magazine})},\n  author={A. Coles and A. Coles and A. Garc\\'ia Olaya and S. Jim\\'enez and C. Linares L\\'opez and S. Sanner and S. Yoon},\n  year={2012},\n  volume={33},\n  number={1}, \n  pages={83--88},\n  url_paper = {https://ssanner.github.io/papers/anu/aim12.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2011\n \n \n (6)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Diverse Retrieval via Greedy Optimization of Expected 1-call@k in a Latent Subtopic Relevance Model.\n \n \n \n \n\n\n \n Sanner, S.; Guo, S.; Graepel, T.; Kharazmi, S.; and Karimi, S.\n\n\n \n\n\n\n In 20th ACM Conference on Information and Knowledge Management (CIKM-11), Glasgow, UK, 2011. \n \n\n\n\n
\n\n\n\n \n \n $\"Diverse$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 21 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:cikm11,\n  author = "S. Sanner and S. Guo and T. Graepel and S. Kharazmi and S. Karimi",\n  year = "2011",\n  title = "Diverse Retrieval via Greedy Optimization of Expected 1-call@k in a Latent Subtopic Relevance Model",\n  booktitle = "20th ACM Conference on Information and Knowledge Management ({CIKM-11})",\n  address = "Glasgow, UK",\n  url_paper = {https://ssanner.github.io/papers/anu/cikm11.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Symbolic Dynamic Programming for Discrete and Continuous State MDPs.\n \n \n \n \n\n\n \n Sanner, S.; Delgado, K. V.; and de Barros , L. N.\n\n\n \n\n\n\n In Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence (UAI-11), Barcelona, Spain, 2011. \n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 8 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai11,\n  author = "S. Sanner and K. V. Delgado and L. Nunes {de Barros}",\n  year = "2011",\n  title = "Symbolic Dynamic Programming for Discrete and Continuous State {MDP}s", \n  booktitle = "Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence ({UAI-11})",\n  address = "Barcelona, Spain",\n  url_paper = {https://ssanner.github.io/papers/anu/cont_mdp.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Sparse Kernel-SARSA(lambda) with an Eligibility Trace.\n \n \n \n \n\n\n \n Robards, M.; Sunehag, P.; Sanner, S.; and Marthi, B.\n\n\n \n\n\n\n In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-11), 2011. \n \n\n\n\n
\n\n\n\n \n \n $\"Sparse$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ecml11,\n  author = "M. Robards and P. Sunehag and S. Sanner and B. Marthi",\n  year = "2011",\n  title = "Sparse Kernel-{SARSA}(lambda) with an Eligibility Trace",\n  booktitle = "Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases ({ECML/PKDD-11})",\n  location = "Athens, Greece",\n  url_paper = {https://ssanner.github.io/papers/anu/kernel_sarsa.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Multi-Evidence Lifted Message Passing with Application to PageRank and the Kalman Filter.\n \n \n \n \n\n\n \n Ahmadi, B.; Kersting, K.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI-11), 2011. \n \n\n\n\n
\n\n\n\n \n \n $\"Multi-Evidence$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai11,\n  author = "B. Ahmadi and K. Kersting and S. Sanner",\n  year = "2011",\n  title = "Multi-Evidence Lifted Message Passing with Application to PageRank and the Kalman Filter", \n  booktitle = "Proceedings of the 22nd International Joint Conference on Artificial Intelligence ({IJCAI-11})",\n  location = "Barcelona, Spain",\n  url_paper = {https://ssanner.github.io/papers/anu/ijcai11.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Efficient Solutions to Factored MDPs with Imprecise Transition Probabilities.\n \n \n \n \n\n\n \n Delgado, K. V.; Sanner, S.; and de Barros , L. N.\n\n\n \n\n\n\n Artificial Intelligence Journal (AIJ), 175: 1498–1527. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Efficient$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:aij11,\n  author = "K. V. Delgado and S. Sanner and L. Nunes {de Barros}",\n  year = "2011",\n  title = "Efficient Solutions to Factored {MDPs} with Imprecise Transition Probabilities",\n  journal = "Artificial Intelligence Journal ({AIJ})",\n  volume = "175",\n  pages = "1498--1527",\n  url_paper = {https://ssanner.github.io/papers/anu/aij11_final.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Using Mathematical Programming to Solve Factored Markov Decision Processes with Imprecise Probabilities.\n \n \n \n \n\n\n \n Delgado, K. V.; de Barros , L. N.; Cozman, F. G.; and Sanner, S.\n\n\n \n\n\n\n International Journal of Approximate Reasoning (IJAR), 52(7): 1000–1017. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:ijar11,\n  author = "K. Valdivia Delgado and L. Nunes {de Barros} and F. G. Cozman and S. Sanner",\n  year = "2011",\n  title = "Using Mathematical Programming to Solve Factored {M}arkov Decision Processes with Imprecise Probabilities",\n  journal = "International Journal of Approximate Reasoning ({IJAR})",\n  volume = "52",\n  number = "7", \n  pages = "1000--1017",\n  url_paper = {https://ssanner.github.io/papers/anu/ijar11_final.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2010\n \n \n (8)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Relational Dynamic Influence Diagram Language (RDDL): Language Description — http://users.cecs.anu.edu.au/ ssanner/IPPC_2011/RDDL.pdf.\n \n \n \n \n\n\n \n Sanner, S.\n\n\n \n\n\n\n 2010.\n Unpublished Manuscript, Australian National University\n\n\n\n
\n\n\n\n \n \n $\"Relational$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@unpublished{sanner:rddl,\n  author = "S. Sanner",\n  title = "{R}elational {D}ynamic {I}nfluence {D}iagram\n{L}anguage ({RDDL}): Language Description --- http://users.cecs.anu.edu.au/~ssanner/IPPC_2011/RDDL.pdf",\n  note = "Unpublished Manuscript, Australian National University",\n  year = "2010",\n  url = "http://users.cecs.anu.edu.au/~ssanner/IPPC_2011/RDDL.pdf"\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Gaussian Process Preference Elicitation.\n \n \n \n \n\n\n \n Bonilla, E.; Guo, S.; and Sanner, S.\n\n\n \n\n\n\n In Advances in Neural Information Processing Systems 24 (NeurIPS-10), Vancouver, Canada, 2010. MIT Press\n \n\n\n\n
\n\n\n\n \n \n $\"Gaussian$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:nips10,\n  author = "E. Bonilla and S. Guo and S. Sanner",\n  title = "Gaussian Process Preference Elicitation",\n  booktitle = "Advances in Neural Information Processing Systems 24 ({NeurIPS-10})",\n  year = "2010",\n  address = "Vancouver, Canada",\n  publisher = "MIT Press",\n  url_paper = {https://ssanner.github.io/papers/anu/gppe_final.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Symbolic Dynamic Programming for First-order POMDPs.\n \n \n \n \n\n\n \n Sanner, S.; and Kersting, K.\n\n\n \n\n\n\n In Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI-10), Atlanta, Georgia, July 19-23 2010. AAAI Press\n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aaai10,\n  AUTHOR =       {S. Sanner and K. Kersting},\n  TITLE =        {Symbolic Dynamic Programming for First-order {POMDP}s},\n  BOOKTITLE =    {Proceedings of the 24th AAAI Conference on Artificial Intelligence ({AAAI-10})},\n  YEAR =         {2010},\n  address =      {Atlanta, Georgia},\n  month =        {July 19-23},\n  publisher =    {AAAI Press},\n  url_paper = {https://ssanner.github.io/papers/anu/fo_pomdp.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda.\n \n \n \n \n\n\n \n Downey, C.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 27th International Conference on Machine Learning (ICML-10), Haifa, Israel, June 21-24 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Temporal$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icml10,\n  AUTHOR =       {C. Downey and S. Sanner},\n  TITLE =        {Temporal Difference {Bayesian} Model Averaging: A {Bayesian} Perspective on Adapting Lambda},\n  BOOKTITLE =    {Proceedings of the 27th International Conference on Machine Learning ({ICML-10})},\n  YEAR =         {2010},\n  address =      {Haifa, Israel},\n  month =        {June 21-24},\n  url_paper = {https://ssanner.github.io/papers/anu/td_bma.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Probabilistic Latent Maximal Marginal Relevance.\n \n \n \n \n\n\n \n Guo, S.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 33rd Annual ACM SIG Information Retrieval Conference (SIGIR-10), Geneva, Switzerland, July 11-15 2010. ACM\n \n\n\n\n
\n\n\n\n \n \n $\"Probabilistic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@INPROCEEDINGS{sanner:sigir10,\n  AUTHOR =       {S. Guo and S. Sanner},\n  TITLE =        {Probabilistic Latent Maximal Marginal Relevance},\n  BOOKTITLE =    {Proceedings of the 33rd Annual ACM SIG Information Retrieval Conference ({SIGIR-10})},\n  YEAR =         {2010},\n  address =      {Geneva, Switzerland},\n  month =        {July 11-15},\n  publisher =    {ACM},\n  url_paper = {https://ssanner.github.io/papers/anu/sigir10.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries.\n \n \n \n \n\n\n \n Guo, S.; and Sanner, S.\n\n\n \n\n\n\n In Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS-10), volume 9, pages 289–296, Sardinia, Italy, May 13-15 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Real-time$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 33 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@INPROCEEDINGS{sanner:aistats10,\n  AUTHOR =       {S. Guo and S. Sanner},\n  TITLE =        {Real-time Multiattribute {Bayesian} Preference Elicitation with Pairwise Comparison Queries},\n  BOOKTITLE =    {Proceedings of the 13th International Conference on Artificial Intelligence and Statistics ({AISTATS-10})},\n  YEAR =         {2010},\n  volume =       {9},\n  pages =        {289--296},\n  address =      {Sardinia, Italy},\n  month =        {May 13-15},\n  url_paper = {https://ssanner.github.io/papers/anu/baypref.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Approximate Dynamic Programming with Affine ADDs.\n \n \n \n \n\n\n \n Sanner, S.; Uther, W.; and Delgado, K. V.\n\n\n \n\n\n\n In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-10), Toronto, Canada, 2010. \n \n\n\n\n
\n\n\n\n \n \n $\"Approximate$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:aamas10,\n  author = "S. Sanner and W. Uther and K. V. Delgado",\n  year = "2010",\n  title = "Approximate Dynamic Programming with {Affine} {ADDs}",\n  booktitle = "Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems ({AAMAS-10})",\n  address = "Toronto, Canada",\n  url_paper = {https://ssanner.github.io/papers/anu/aadd_approx.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Symbolic dynamic programming.\n \n \n \n \n\n\n \n Sanner, S.; and Kersting, K.\n\n\n \n\n\n\n In Encyclopedia of Machine Learning, pages 946–954. Springer-Verlag, 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@incollection{sanner:enc10, \nauthor = "S. Sanner and K. Kersting",\nyear = "2010",\ntitle = "Symbolic dynamic programming",\neditors = "C. Sammut", \npages = "946--954",\nbooktitle = {Encyclopedia of Machine Learning}, \npublisher = "Springer-Verlag",\n  url_paper = {https://ssanner.github.io/papers/anu/SDP_MLEnc.pdf}\n} \n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2009\n \n \n (3)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Efficient Solutions to Factored MDPs with Imprecise Transition Probabilities.\n \n \n \n \n\n\n \n Delgado, K. V.; Sanner, S.; de Barros, L. N.; and Cozman, F. G.\n\n\n \n\n\n\n In Proceedings of the 19th Conference on Automated Planning and Scheduling (ICAPS-09), 2009. \n \n\n\n\n
\n\n\n\n \n \n $\"Efficient$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icaps09,\n  author = "K. V. Delgado and S. Sanner and L. Nunes de Barros and F. G. Cozman",\n  year = "2009",\n  title = "Efficient Solutions to Factored {MDP}s with Imprecise Transition Probabilities",\n  booktitle = "Proceedings of the 19th Conference on Automated Planning and Scheduling ({ICAPS-09})",\n  pdf = "http://users.cecs.anu.edu.au/~ssanner/Papers/fact_mdpip.pdf",\n  url_paper = {https://ssanner.github.io/papers/anu/fact_mdpip.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Bayesian Real-time Dynamic Programming.\n \n \n \n \n\n\n \n Sanner, S.; Goetschalckx, R.; Driessens, K.; and Shani, G.\n\n\n \n\n\n\n In Boutilier, editor(s), 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pages 1–8, Pasadena, USA, July 2009. \n \n\n\n\n
\n\n\n\n \n \n $\"Bayesian$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 9 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings {sanner:ijcai09,\n  author = "S. Sanner and R. Goetschalckx and K. Driessens and G. Shani",\n  pages = "1--8",\n  year = "2009",\n  booktitle = "21st International Joint Conference on Artificial Intelligence ({IJCAI-09})",\n  address = "Pasadena, USA",\n  editor = "Boutilier",\n  pdf = "https://ssanner.github.io/papers/anu/ijcai09.pdf",\n  title = "{Bayesian} Real-time Dynamic Programming",\n  month = "July",\n  url_paper = {https://ssanner.github.io/papers/anu/ijcai09.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Practical Solution Techniques for First-order MDPs.\n \n \n \n \n\n\n \n Sanner, S.; and Boutilier, C.\n\n\n \n\n\n\n Artificial Intelligence Journal (AIJ),748-788. April 2009.\n Recipient of the 2014 Artificial Intelligence Journal (AIJ) Prominent Paper Award.\n\n\n\n
\n\n\n\n \n \n $\"Practical$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 44 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article {sanner:aij09,\n  author = "S. Sanner and C. Boutilier",\n  year = "2009",\n  journal = "Artificial Intelligence Journal ({AIJ})",\n  title = "Practical Solution Techniques for First-order {MDP}s",\n  pages = "748-788",\n  note = {Recipient of the 2014 Artificial Intelligence Journal (AIJ) Prominent Paper Award.},\n  pdf = "https://ssanner.github.io/papers/anu/aij08.pdf",\n  month = "April",\n  url_paper = {https://ssanner.github.io/papers/anu/aij08.pdf} \n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2008\n \n \n (4)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Reinforcement learning with the use of costly features.\n \n \n \n \n\n\n \n Goetschalckx, R.; Sanner, S.; and Driessens, K.\n\n\n \n\n\n\n Lecture Notes in Computer Science, 5323: 124–135. November 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Reinforcement$ Paper\n \n \n \n $\"Reinforcement$ paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{sanner:ewrl08,\n  author = "R. Goetschalckx and S. Sanner and K. Driessens",\n  title = "Reinforcement learning with the use of costly features",\n  journal = {Lecture Notes in Computer Science},\n  volume = "5323",\n  pages = "124--135",\n  month = Nov,\n  year = "2008",\n  doi = "10.1007/978-3-540-89722-4\\_{}10",\n  url = "https://lirias.kuleuven.be/handle/123456789/199408",\n  url_paper = {https://ssanner.github.io/papers/anu/ewrl08.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Cost-sensitive parsimonious linear regression.\n \n \n \n \n\n\n \n Goetschalckx, R.; Sanner, S.; and Driessens, K.\n\n\n \n\n\n\n In Proceedings of the 8th IEEE International Conference on Data Mining (ICDM-08), pages 809–814, 2008. IEEE Computer Society\n \n\n\n\n
\n\n\n\n \n \n $\"Cost-sensitive$ Paper\n \n \n \n $\"Cost-sensitive$ paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icdm08,\n  author = "R. Goetschalckx and S. Sanner and K. Driessens",\n  title = "Cost-sensitive parsimonious linear regression",\n  booktitle = "Proceedings of the 8th IEEE International Conference on Data Mining ({ICDM-08})",\n  publisher = "IEEE Computer Society",\n  pages = "809--814",\n  year = "2008",\n  doi = "10.1109/ICDM.2008.76",\n  url = "https://lirias.kuleuven.be/handle/123456789/199410",\n  url_paper = {https://ssanner.github.io/papers/anu/icdm08.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Reinforcement Learning with the Use of Costly Features.\n \n \n \n \n\n\n \n Goetschalckx, R.; Sanner, S.; and Driessens, K.\n\n\n \n\n\n\n In European Conference on Artificial Intelligence (ECAI-08), 2008. \n \n\n\n\n
\n\n\n\n \n \n $\"Reinforcement$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ecai08,\nauthor = "R. Goetschalckx and S. Sanner and K. Driessens",\nyear = "2008",\ntitle = "Reinforcement Learning with the Use of Costly Features",\nbooktitle = "European Conference on Artificial Intelligence ({ECAI-08})",\npdf = "http://users.rsise.anu.edu.au/&ntilde;ssanner/Papers/ecai08.pdf",\n  url_paper = {https://ssanner.github.io/papers/anu/ecai08.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n First-order Decision-theoretic Planning in Structured Relational Environments.\n \n \n \n \n\n\n \n Sanner, S.\n\n\n \n\n\n\n Ph.D. Thesis, University of Toronto, Toronto, ON, Canada, March 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"First-order$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 16 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@phdthesis{sanner:phd,\n    author = "S. Sanner",\n    title = "{First-order Decision-theoretic Planning in Structured Relational Environments}",\n    school = "University of Toronto, Toronto, ON, Canada",\n    month = "March",\n    year = "2008",\n    url_paper = {https://ssanner.github.io/papers/anu/Sanner_Scott_P_200803_PhD_thesis.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2007\n \n \n (2)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Approximate solution techniques for factored first-order MDPs.\n \n \n \n \n\n\n \n Sanner, S.; and Boutilier, C.\n\n\n \n\n\n\n In Proceedings of the 17th Conference on Automated Planning and Scheduling (ICAPS-07), 2007. \n \n\n\n\n
\n\n\n\n \n \n $\"Approximate$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icaps07,\nauthor = "S. Sanner and C. Boutilier",\nyear = "2007",\ntitle = "Approximate solution techniques for factored first-order {MDP}s",\nbooktitle = "Proceedings of the 17th Conference on Automated Planning and Scheduling ({ICAPS-07})",\n  url_paper = {https://ssanner.github.io/papers/anu/icaps07.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Learning CRFs with hierarchical features: An application to the game of Go.\n \n \n \n \n\n\n \n Sanner, S.; Graepel, T.; Herbrich, R.; and Minka, T.\n\n\n \n\n\n\n In Proceedings of the Workshop on Constrained Optimization and Structured Output Spaces (WCSOS-07), 2007. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 5 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icml07, \nauthor = "S. Sanner and T. Graepel and R. Herbrich and T. Minka",\nyear = "2007",\ntitle = "Learning {CRF}s with hierarchical features: An application to the game of Go",\nbooktitle = "Proceedings of the Workshop on Constrained Optimization and Structured Output Spaces ({WCSOS-07})",\n  url_paper = {https://ssanner.github.io/papers/anu/crfgo.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2006\n \n \n (3)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Practical linear value-approximation techniques for first-order MDPs.\n \n \n \n \n\n\n \n Sanner, S.; and Boutilier, C.\n\n\n \n\n\n\n In Proceedings of the 22nd Conference on Uncertainty in AI (UAI-06), 2006. \n \n\n\n\n
\n\n\n\n \n \n $\"Practical$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai06,\nauthor = "S. Sanner and C. Boutilier",\nyear = "2006",\ntitle = "Practical linear value-approximation techniques for first-order {MDP}s",\nbooktitle = "Proceedings of the 22nd Conference on Uncertainty in AI ({UAI-06})",\n  url_paper = {https://ssanner.github.io/papers/anu/uai06.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n An ordered theory resolution calculus for hybrid reasoning in first-order extensions of description logic.\n \n \n \n \n\n\n \n Sanner, S.; and McIlraith, S.\n\n\n \n\n\n\n In Proceedings of the 10th International Conference on Principles of Knowledge Representation and Reasoning (KR-06), 2006. \n \n\n\n\n
\n\n\n\n \n \n $\"An$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 22 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:kr06,\nauthor = "S. Sanner and S. McIlraith",\nyear = "2006",\ntitle = "An ordered theory resolution calculus for hybrid reasoning in first-order extensions of description logic",\nbooktitle = "Proceedings of the 10th International Conference on Principles of Knowledge Representation and Reasoning ({KR-06})",\n  url_paper = {https://ssanner.github.io/papers/anu/dlfol_kr06.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Online feature discovery in relational reinforcement learning.\n \n \n \n \n\n\n \n Sanner, S.\n\n\n \n\n\n\n In Proceedings of the Open Problems in Statistical Relational Learning Workshop (SRL-06), 2006. \n \n\n\n\n
\n\n\n\n \n \n $\"Online$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:srl06,\nauthor = "S. Sanner",\nyear = "2006",\ntitle = "Online feature discovery in relational reinforcement learning",\nbooktitle = "Proceedings of the Open Problems in Statistical Relational Learning Workshop ({SRL-06})",\n  url_paper = {https://ssanner.github.io/papers/anu/icml06_srl_ws.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2005\n \n \n (4)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Affine algebraic decision diagrams (AADDs) and their application to structured probabilistic inference.\n \n \n \n \n\n\n \n Sanner, S.; and McAllester, D.\n\n\n \n\n\n\n In Proceedings of the 19th International Joint Conference on AI (IJCAI-05), 2005. \n \n\n\n\n
\n\n\n\n \n \n $\"Affine$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:ijcai05,\nauthor = "S. Sanner and D. McAllester",\nyear = "2005",\ntitle = "Affine algebraic decision diagrams ({AADD}s) and their application to structured probabilistic inference",\nbooktitle = "Proceedings of the 19th International Joint Conference on {AI} ({IJCAI-05})",\n  url_paper = {https://ssanner.github.io/papers/anu/aadd.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Approximate linear programming for first-order MDPs.\n \n \n \n \n\n\n \n Sanner, S.; and Boutilier, C.\n\n\n \n\n\n\n In Proceedings of the 21st Conference on Uncertainty in AI (UAI-05), 2005. \n \n\n\n\n
\n\n\n\n \n \n $\"Approximate$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai05,\nauthor = "S. Sanner and C. Boutilier",\nyear = "2005",\ntitle = "Approximate linear programming for first-order {MDP}s",\nbooktitle = "Proceedings of the 21st Conference on Uncertainty in {AI} ({UAI-05})",\n  url_paper = {https://ssanner.github.io/papers/anu/uai05.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Simultaneous learning of structure and value in relational reinforcement learning.\n \n \n \n \n\n\n \n Sanner, S.\n\n\n \n\n\n\n In Proceedings of the Rich Representations for Relational Reinforcement Learning Workshop (RRfRL-05), 2005. \n \n\n\n\n
\n\n\n\n \n \n $\"Simultaneous$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:rrfrl05,\nauthor = "S. Sanner", \nyear = "2005",\ntitle = "Simultaneous learning of structure and value in relational reinforcement learning",\nbooktitle = "Proceedings of the Rich Representations for Relational Reinforcement Learning Workshop ({RRfRL-05})",\n  url_paper = {https://ssanner.github.io/papers/anu/icml05_ws.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Future directions for first-order decision-theoretic planning.\n \n \n \n \n\n\n \n Sanner, S.\n\n\n \n\n\n\n Technical Report University of Toronto, 2005.\n \n\n\n\n
\n\n\n\n \n \n $\"Future$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@techreport{sanner:rp05,\nauthor = "S. Sanner",\nyear = "2005",\ntitle = "Future directions for first-order decision-theoretic planning",\ninstitution = "University of Toronto",\ntype = "{Research Proposal}",\n  url_paper = {https://ssanner.github.io/papers/anu/research_prop.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2004\n \n \n (2)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Relational and first-order decision-theoretic planning: Foundations and future directions.\n \n \n \n \n\n\n \n Sanner, S.\n\n\n \n\n\n\n Technical Report University of Toronto, 2004.\n \n\n\n\n
\n\n\n\n \n \n $\"Relational$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 25 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@techreport{sanner:dr04,\nauthor = "S. Sanner",\nyear = "2004",\ntitle = "Relational and first-order decision-theoretic planning: Foundations and future directions",\ntype = "{Depth Report}",\ninstitution = "University of Toronto",\n  url_paper = {https://ssanner.github.io/papers/anu/sanner-depth.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Refutation-complete binary decision diagrams.\n \n \n \n \n\n\n \n Sanner, S.\n\n\n \n\n\n\n Technical Report University of Toronto, 2004.\n \n\n\n\n
\n\n\n\n \n \n $\"Refutation-complete$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@techreport{sanner:unpub04, \nauthor = "S. Sanner",\nyear = "2004",\ntitle = "Refutation-complete binary decision diagrams",\ntype = "{Unpublished Manuscript}",\ninstitution = "University of Toronto",\n  url_paper = {https://ssanner.github.io/papers/anu/rcbdd.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2003\n \n \n (1)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Towards practical taxonomic classification for description logics on the Semantic Web.\n \n \n \n \n\n\n \n Sanner, S.\n\n\n \n\n\n\n Technical Report KSL-03-06, Stanford University, Knowledge Systems Lab, 2003.\n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@techreport{sanner:tr03,\nauthor = "S. Sanner",\nyear = "2003",\ntitle = "Towards practical taxonomic classification for description logics on the {Semantic Web}",\ntype = "{Technical Report}", \ninstitution = "Stanford University, Knowledge Systems Lab",\nnumber = "KSL-03-06",\n  url_paper = {https://ssanner.github.io/papers/anu/ksl0301.pdf}\n}\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2002\n \n \n (2)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Learning hierarchical object maps of non-stationary environments with mobile robots.\n \n \n \n \n\n\n \n Anguelov, D.; Biswas, R.; Koller, D.; Limketkai, B.; Sanner, S.; and Thrun, S.\n\n\n \n\n\n\n In Proceedings of the 18th Conference on Uncertainty in AI (UAI-02), 2002. \n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:uai02,\nauthor = "D. Anguelov and R. Biswas and D. Koller and B. Limketkai and S. Sanner and S. Thrun",\nyear = "2002",\ntitle = "Learning hierarchical object maps of non-stationary environments with mobile robots",\nbooktitle = "Proceedings of the 18th Conference on Uncertainty in {AI} ({UAI-02})",\n  url_paper = {https://ssanner.github.io/papers/anu/anguelov.uai02.pdf}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Towards object mapping in dynamic environments with mobile robots.\n \n \n \n \n\n\n \n Biswas, R.; Limketkai, B.; Sanner, S.; and Thrun, S.\n\n\n \n\n\n\n In Proceedings of the Conference on Intelligent Robots and Systems (IROS-02), 2002. \n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:iros02,\nauthor = "R. Biswas and B. Limketkai and S. Sanner and S. Thrun",\nyear = "2002",\ntitle = "Towards object mapping in dynamic environments with mobile robots",\nbooktitle = "Proceedings of the Conference on Intelligent Robots and Systems ({IROS-02})",\n  url_paper = {https://ssanner.github.io/papers/anu/biswas.objects02.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n

\n \n 2000\n \n \n (1)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Achieving efficient and cognitively plausible learning in backgammon.\n \n \n \n \n\n\n \n Sanner, S.; Anderson, J. R.; Lebiere, C.; and Lovett, M.\n\n\n \n\n\n\n In Proceedings of the 17th International Conference on Machine Learning (ICML-00), 2000. \n \n\n\n\n
\n\n\n\n \n \n $\"Achieving$ paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@inproceedings{sanner:icml00,\nauthor = "S. Sanner and J. R. Anderson and C. Lebiere and M. Lovett",\nyear = "2000",\ntitle = "Achieving efficient and cognitively plausible learning in backgammon",\nbooktitle = "Proceedings of the 17th International Conference on Machine Learning ({ICML-00})",\n  url_paper = {https://ssanner.github.io/papers/anu/ICML2000.pdf}\n}\n\n

\n\n\n\n

\n\n\n\n\n\n

\n\n\n\n\n

\n\n\n \n\n \n \n \n \n\n