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  2024 (2)
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations. Xu, Y., Li, W., Vaezipoor, P., Sanner, S., & Khalil, E. B. Transactions on Machine Learning Research. Feb 2024.
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations [link] url   link   bibtex   1 download  
Bayesian Inference with Complex Knowledge Graph Evidence. Toroghi, A., & Sanner, S. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, Canada, 2024.
Bayesian Inference with Complex Knowledge Graph Evidence [pdf] paper   Bayesian Inference with Complex Knowledge Graph Evidence [link] github   link   bibtex   28 downloads  
  2023 (20)
COUNT: COntrastive UNlikelihood Text Style Transfer for Text Detoxification. Pour, M. M. A., Farinneya, P., Bharadwaj, M., Verma, N., Pesaranghader, A., & Sanner, S. In Findings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP-23), Singapore, 2023. Association for Computational Linguistics
COUNT: COntrastive UNlikelihood Text Style Transfer for Text Detoxification [pdf] paper   COUNT: COntrastive UNlikelihood Text Style Transfer for Text Detoxification [link] github   link   bibtex   11 downloads  
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. Sanner, S., Balog, K., Radlinski, F., Wedin, B., & Dixon, L. In Proceedings of 17th ACM Conference on Recommender Systems (RecSys-23), Singapore, 2023.
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences [pdf] paper   Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences [link] arxiv   link   bibtex   42 downloads  
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization. Jeong, J., Wang, X., Gimelfarb, M., Kim, H., Abdulhai, B., & Sanner, S. In Proceedings of the International Conference on Learning Representations (ICLR-23), Kigali, Rwanda, 2023.
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization [pdf] paper   Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization [link] github   link   bibtex   48 downloads  
Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects. Low, S. M., Kumar, A., & Sanner, S. In Proceedings of the 33rd Conference on Automated Planning and Scheduling (ICAPS-23), Prague, Czech Republic, 2023.
Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects [pdf] paper   link   bibtex   11 downloads  
Recipe-MPR: A Test Collection for Evaluating Multi-aspect Preference-based Natural Language Retrieval. Zhang, H., Korikov, A., Farinneya, P., Pour, M. M. A., Bharadwaj, M., Pesaranghader, A., Huang, X. Y., Lok, Y. X., Wang, Z., Jones, N., & Sanner, S. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-23), Taipei, Taiwan, 2023.
Recipe-MPR: A Test Collection for Evaluating Multi-aspect Preference-based Natural Language Retrieval [pdf] paper   Recipe-MPR: A Test Collection for Evaluating Multi-aspect Preference-based Natural Language Retrieval [link] github   link   bibtex   52 downloads  
Bayesian Knowledge-driven Critiquing with Indirect Evidence. Toroghi, A., Floto, G., Tang, Z., & Sanner, S. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-23), Taipei, Taiwan, 2023.
Bayesian Knowledge-driven Critiquing with Indirect Evidence [pdf] paper   Bayesian Knowledge-driven Critiquing with Indirect Evidence [link] github   link   bibtex   30 downloads  
Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval. Pour, M. M. A., Farinneya, P., Toroghi, A., Korikov, A., Pesaranghader, A., Sajed, T., Bharadwaj, M., Mavrin, B., & Sanner, S. In Proceedings of the 45th European Conference on IR Research (ECIR-23), Dublin, Ireland, 2023.
Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval [pdf] paper   Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval [link] github   Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval [link] data   link   bibtex   29 downloads  
DiffuDetox: A Mixed Diffusion Model for Text Detoxification. Floto, G., Pour, M. M. A., Farinneya, P., Tang, Z., Pesaranghader, A., Bharadwaj, M., & Sanner, S. In Findings of the Association for Computational Linguistics: ACL-23, pages 7566–7574, 2023. Association for Computational Linguistics
DiffuDetox: A Mixed Diffusion Model for Text Detoxification [link] url   DiffuDetox: A Mixed Diffusion Model for Text Detoxification [pdf] paper   link   bibtex   13 downloads  
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus. Xu, Y., Khalil, E. B., & Sanner, S. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI-23), Washington D.C., USA, 2023.
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus [pdf] paper   Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus [link] github   link   bibtex   60 downloads  
Scalable and Globally Optimal Generalized L1 k-center Clustering via Constraint Generation in Mixed Integer Linear Programming. Chembu, A., Sanner, S., Khurram, H., & Kumar, A. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI-23), Washington D.C., USA, 2023.
Scalable and Globally Optimal Generalized L1 k-center Clustering via Constraint Generation in Mixed Integer Linear Programming [pdf] paper   Scalable and Globally Optimal Generalized L1 k-center Clustering via Constraint Generation in Mixed Integer Linear Programming [link] github   link   bibtex   45 downloads  
Scalable and Near-Optimal Epsilon-tube Clusterwise Regression. Chembu, A., Sanner, S., & Khalil, E. In Proceedings of the 20th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-23), Nice, France, 2023.
Scalable and Near-Optimal Epsilon-tube Clusterwise Regression [pdf] paper   Scalable and Near-Optimal Epsilon-tube Clusterwise Regression [link] github   link   bibtex   14 downloads  
A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination. Jeong, J., Sanner, S., & Kumar, A. In Proceedings of the 20th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-23), Nice, France, 2023.
A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination [pdf] paper   A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination [link] github   link   bibtex   16 downloads  
Towards Dialogue Modeling Beyond Text. Wu, T., Zhou, Y., Ling, W., Yang, H., Veloso, J., Sun, L., Huang, R., Guimaraes, N., & Sanner, S. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-23), Rhodes, Greece, 2023.
Towards Dialogue Modeling Beyond Text [pdf] paper   link   bibtex   10 downloads  
Towards Understanding and Mitigating Unintended Biases in Language Model-driven Conversational Recommendation. Shen, T., Li, J., Bouadjenek, M. R., Mai, Z., & Sanner, S. Information Processing & Management, 60(1): 103139. 2023.
Towards Understanding and Mitigating Unintended Biases in Language Model-driven Conversational Recommendation [link] url   Towards Understanding and Mitigating Unintended Biases in Language Model-driven Conversational Recommendation [pdf] paper   Towards Understanding and Mitigating Unintended Biases in Language Model-driven Conversational Recommendation [link] blog   Towards Understanding and Mitigating Unintended Biases in Language Model-driven Conversational Recommendation [link] github   link   bibtex   65 downloads  
User Experience and The Role of Personalization in Critiquing-Based Conversational Recommendation. Rana, A., Sanner, S., Bouadjenek, M. R., Dicarlantonio, R., & Farmaner, G. ACM Transactions on the Web (TWeb). May 2023. Accepted
User Experience and The Role of Personalization in Critiquing-Based Conversational Recommendation [link] url   User Experience and The Role of Personalization in Critiquing-Based Conversational Recommendation [pdf] paper   doi   link   bibtex   12 downloads  
A User-Centric Analysis of Social Media for Stock Market Prediction. Bouadjenek, M. R., Sanner, S., & Wu, G. ACM Transactions on the Web, 17: 1–22. Mar 2023.
A User-Centric Analysis of Social Media for Stock Market Prediction [link] url   A User-Centric Analysis of Social Media for Stock Market Prediction [pdf] preprint   link   bibtex   2 downloads  
TransCAM: Transformer Attention-Based CAM Refinement for Weakly Supervised Semantic Segmentation. Li, R., Mai, Z., Zhang, Z., Jang, J., & Sanner, S. Journal of Visual Communication and Image Representation, 92(C): 103800. Apr 2023.
TransCAM: Transformer Attention-Based CAM Refinement for Weakly Supervised Semantic Segmentation [link] url   TransCAM: Transformer Attention-Based CAM Refinement for Weakly Supervised Semantic Segmentation [pdf] preprint   TransCAM: Transformer Attention-Based CAM Refinement for Weakly Supervised Semantic Segmentation [link] github   link   bibtex   16 downloads  
eMARLIN: Distributed Coordinated Adaptive Traffic Signal Control with Topology-Embedding Propagation. Wang, X., Taitler, A., Smirnov, I., Sanner, S., & Abdulhai, B. Transportation Research Record,1–14. 2023. Accepted.
eMARLIN: Distributed Coordinated Adaptive Traffic Signal Control with Topology-Embedding Propagation [link] url   link   bibtex   5 downloads  
A Comparative Evaluation of Established and Contemporary Deep Learning Traffic Prediction Methods. Ting, T. J., Sanner, S., & Abdulhai, B. In Dia, H., editor(s), Handbook on Artificial Intelligence and Transport, 1, pages 14–46. Edward Elgar Publishing, 2023.
A Comparative Evaluation of Established and Contemporary Deep Learning Traffic Prediction Methods [link] url   link   bibtex   3 downloads  
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. Wang, X., Abdulhai, B., & Sanner, S. In Dia, H., editor(s), Handbook on Artificial Intelligence and Transport, 17, pages 482–532. Edward Elgar Publishing, 2023.
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 [link] url   link   bibtex   1 download  
  2022 (11)
Learning to Follow Instructions in Text-Based Games. Tuli, M., Li, A., Vaezipoor, P., Klassen, T., Sanner, S., & McIlraith, S. In Proceedings of the 36th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-22), New Orleans, USA, 2022.
Learning to Follow Instructions in Text-Based Games [pdf] paper   link   bibtex   54 downloads  
An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming. Jeong, J., Jaggi, P., Butler, A., & Sanner, S. In Proceedings of the 39th International Conference on Machine Learning (ICML-22), Baltimore, USA, 2022.
An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming [pdf] paper   link   bibtex   31 downloads  
Mitigating the Filter Bubble while Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems. Gao, Z., Shen, T., Mai, Z., Bouadjenek, M. R., Waller, I., Anderson, A., Bodkin, R., & Sanner, S. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-22), Madrid, Spain, 2022.
Mitigating the Filter Bubble while Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems [pdf] paper   link   bibtex   39 downloads  
Distributional Contrastive Embedding for Clarification-based Conversational Critiquing. Shen, T., Mai, Z., Wu, G., & Sanner, S. In Proceedings of the 31st International Conference on the World Wide Web (WWW-22), Online, 2022.
Distributional Contrastive Embedding for Clarification-based Conversational Critiquing [pdf] paper   link   bibtex   23 downloads  
A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs. Patton, N., Jeong, J., Gimelfarb, M., & Sanner, S. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), Online, 2022.
A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs [pdf] paper   link   bibtex   23 downloads  
Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs. Low, S., Kumar, A., & Sanner, S. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), Online, 2022.
Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs [pdf] paper   link   bibtex   6 downloads  
Distributional Reward Shaping: Point Estimates Are All You Need. Gimelfarb, M., Sanner, S., & Lee, C. In Proceedings of the fifth Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM-22), Providence, USA, 2022.
Distributional Reward Shaping: Point Estimates Are All You Need [pdf] paper   link   bibtex   3 downloads  
What's in a (Data) Type? Meaningful Type Safety for Data Science. Moher, R., Gruninger, M., & Sanner, S. In Proceedings of the 16th International Conference on Research Challenges in Information Science (RCIS-22), Barcelona, Spain, 2022.
What's in a (Data) Type? Meaningful Type Safety for Data Science [pdf] paper   link   bibtex   16 downloads  
Arbitrary conditional inference in variational autoencoders via fast prior network training. Wu, G., Domke, J., & Sanner, S. Machine Learning. 2022. In press.
Arbitrary conditional inference in variational autoencoders via fast prior network training [link] url   Arbitrary conditional inference in variational autoencoders via fast prior network training [pdf] preprint   link   bibtex   13 downloads  
Online Continual Learning in Image Classification: An Empirical Survey. Mai, Z., Li, R., Jeong, J., Quispe, D., Kim, H., & Sanner, S. Neurocomputing, 469: 28–51. 2022.
Online Continual Learning in Image Classification: An Empirical Survey [link] url   Online Continual Learning in Image Classification: An Empirical Survey [pdf] preprint   link   bibtex   14 downloads  
A Longitudinal Study of Topic Classification on Twitter. Bouadjenek, M. R., Sanner, S., Iman, Z., Xie, L., & Shi, X. PeerJ Computer Science. 2022. Accepted.
A Longitudinal Study of Topic Classification on Twitter [link] url   A Longitudinal Study of Topic Classification on Twitter [pdf] preprint   link   bibtex   14 downloads  
  2021 (16)
Risk-Aware Transfer in Reinforcement Learning using Successor Features. Gimelfarb, M., Barreto, A., Sanner, S., & Lee, C. In Proceedings of the 35th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-21), Online, 2021.
Risk-Aware Transfer in Reinforcement Learning using Successor Features [pdf] paper   link   bibtex   4 downloads  
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models. Sui, Y., Wu, G., & Sanner, S. In Proceedings of the 35th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-21), Online, 2021.
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models [pdf] paper   link   bibtex   23 downloads  
Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts. Gimelfarb, M., Sanner, S., & Lee, C. In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence (UAI-21), Online, 2021.
Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts [pdf] paper   link   bibtex   19 downloads  
Bayesian Experience Reuse for Learning from Multiple Demonstrators. Gimelfarb, M., Sanner, S., & Lee, C. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Online, 2021.
Bayesian Experience Reuse for Learning from Multiple Demonstrators [pdf] paper   link   bibtex   32 downloads  
Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions. Jeong, J., Jaggi, P., & Sanner, S. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Online, 2021.
Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions [pdf] paper   link   bibtex   38 downloads  
A Workflow Analysis of Context-driven Conversational Recommendation. Lyu, S., Rana, A., Sanner, S., & Bouadjenek, M. R. In Proceedings of the 30th International Conference on the World Wide Web (WWW-21), Ljubljana, Slovenia, 2021.
A Workflow Analysis of Context-driven Conversational Recommendation [pdf] paper   link   bibtex   129 downloads  
Bayesian Critiquing with Keyphrase Activation Vectors for VAE-based Recommender Systems. Yang, H., Shen, T., & Sanner, S. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-21), Online, 2021.
Bayesian Critiquing with Keyphrase Activation Vectors for VAE-based Recommender Systems [pdf] paper   link   bibtex   115 downloads  
Bayesian Preference Elicitation with Keyphase-Item Coembeddings for Interactive Recommendation. Yang, H., Sanner, S., Wu, G., & Zhou, J. P. In Proceedings of the the 29th Conference on User Modeling, Adaptation and Personalization (UMAP-21), Online, 2021.
Bayesian Preference Elicitation with Keyphase-Item Coembeddings for Interactive Recommendation [pdf] paper   link   bibtex   62 downloads  
Online Class-Incremental Continual Learning with Adversarial Shapley Value. Shim, D., Mai, Z., Jeong, J., Sanner, S., Kim, H., & Jang, J. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21), Online, 2021.
Online Class-Incremental Continual Learning with Adversarial Shapley Value [pdf] paper   link   bibtex   78 downloads  
Revisiting Random Forests in a Comparative Evaluation of Graph Convolutional Neural Network Variants for Traffic Prediction. Ting, T. J., Li, X., Sanner, S., & Abdulhai, B. In 24th IEEE International Intelligent Transportation Systems Conference, ITSC 2021, pages 1259–1265, Indianapolis, USA, 2021. IEEE
link   bibtex  
Microscopic Model-Based RL Approaches for Traffic Signal Control Generalize Better than Model-Free RL Approaches. Jaggi, P., Wang, X., Carrara, N., Sanner, S., & Abdulhai, B. In 24th IEEE International Intelligent Transportation Systems Conference, ITSC 2021, pages 2525–2532, Indianapolis, USA, 2021. IEEE
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Development and Evaluation of Data-driven Controls for Residential Smart Thermostats. Huchuk, B., Sanner, S., & O'Brien, W. Energy and Buildings,111201. 2021.
Development and Evaluation of Data-driven Controls for Residential Smart Thermostats [link] url   link   bibtex   7 downloads  
Evaluation of Data-driven Thermal Models for Multi-hour Predictions using Residential Smart Thermostat Data. Huchuk, B., Sanner, S., & O'Brien, W. Journal of Building Performance Simulation. 2021.
Evaluation of Data-driven Thermal Models for Multi-hour Predictions using Residential Smart Thermostat Data [link] url   link   bibtex   12 downloads  
Reading the City through its Neighbourhoods: Deep text embeddings of Yelp reviews as a basis for determining similarity and change. Olson, A. W., Calderon-Figueroa, F., Bidian, O., Silver, D., & Sanner, S. Cities, 110: 103045. March 2021.
Reading the City through its Neighbourhoods: Deep text embeddings of Yelp reviews as a basis for determining similarity and change [link] url   link   bibtex   26 downloads  
Data Analytics for Cybersecurity Enhancement of Transformer Protection. Jahromi, M. Z., Jahromi, A. A., Kundur, D., Sanner, S., & Kassouf, M. SIGENERGY Energy Inform. Rev., 1(1): 12–19. dec 2021.
Data Analytics for Cybersecurity Enhancement of Transformer Protection [link] url   link   bibtex   2 downloads  
A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays. Khaw, Y. M., Jahromi, A. A., Arani, M. F. M., Sanner, S., Kundur, D., & Kassouf, M. IEEE Transactions on Smart Grid, 12(3): 2554–2565. 2021.
A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays [link] url   link   bibtex   14 downloads  
  2020 (11)
A Ranking Optimization Approach to Latent Linear Critiquing in Conversational Recommender Systems. Li, H., Sanner, S., Luo, K., & Wu, G. In Proceedings of the 14th International ACM Conference on Recommender Systems (RecSys-20), Online, 2020.
A Ranking Optimization Approach to Latent Linear Critiquing in Conversational Recommender Systems [pdf] paper   link   bibtex   37 downloads  
Deep Critiquing for VAE-based Recommender Systems. Luo, K., Yang, H., Wu, G., & Sanner, S. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-20), Xi'an, China, 2020.
Deep Critiquing for VAE-based Recommender Systems [pdf] paper   link   bibtex   137 downloads  
Latent Linear Critiquing for Conversational Recommender Systems. Luo, K., Sanner, S., Wu, G., Li, H., & Yang, H. In Proceedings of the 29th International Conference on the World Wide Web (WWW-20), Taipei, Taiwan, 2020.
Latent Linear Critiquing for Conversational Recommender Systems [pdf] paper   link   bibtex   76 downloads  
Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models. Say, B., & Sanner, S. Artificial Intelligence Journal (AIJ), 285: 103291. August 2020.
Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models [link] paper   Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models [link] arxiv   link   bibtex   38 downloads  
Scalable Planning with Deep Neural Network Learned Transition Models. Wu, G., Say, B., & Sanner, S. Journal of Artificial Intelligence Research (JAIR), 68. July 2020.
Scalable Planning with Deep Neural Network Learned Transition Models [pdf] paper   link   bibtex   53 downloads  
Mitigating the Impact of Light Rail on Urban Traffic Networks using Mixed Integer Linear Programming. Guilliard, I., Trevizan, F., & Sanner, S. IET Intelligent Transport Systems, 14(6): 523–533. 2020.
Mitigating the Impact of Light Rail on Urban Traffic Networks using Mixed Integer Linear Programming [pdf] paper   link   bibtex   19 downloads  
Relevance- and Interface-driven Clustering for Visual Information Retrieval. Bouadjenek, M. R., Sanner, S., & Du, Y. Information Systems, 94: 101592. December 2020.
Relevance- and Interface-driven Clustering for Visual Information Retrieval [link] url   Relevance- and Interface-driven Clustering for Visual Information Retrieval [pdf] paper   Relevance- and Interface-driven Clustering for Visual Information Retrieval [pdf] preprint   link   bibtex   54 downloads  
Classification and Regression via Integer Optimization for Neighborhood Change. Olson, A. W., Zhang, K., Calderon-Figueroa, F., Yakubov, R., Sanner, S., Silver, D., & Arribas-Bel, D. Geographical Analysis. 2020.
Classification and Regression via Integer Optimization for Neighborhood Change [link] url   Classification and Regression via Integer Optimization for Neighborhood Change [pdf] paper   link   bibtex   32 downloads  
Exploring smart thermostat users' schedule override behaviors and the energy consequences. Huchuk, B., O'Brien, W., & Sanner, S. Science and Technology for the Built Environment. 2020.
Exploring smart thermostat users' schedule override behaviors and the energy consequences [link] url   link   bibtex   8 downloads  
A Comparative Evaluation of Unsupervised Deep Architectures for Intrusion Detection in Sequential Data Streams. Sovilj, D., Budnarain, P., Sanner, S., Salmon, G., & Rao, M. Expert Systems With Applications, 159: 113577. November 2020.
A Comparative Evaluation of Unsupervised Deep Architectures for Intrusion Detection in Sequential Data Streams [pdf] paper   link   bibtex   74 downloads  
Stochastic Planning and Lifted Inference. Khardon, R., & Sanner, S. In Van den Broeck, G., Kersting, K., Natarajan, S., & Poole, D., editor(s), An Introduction to Lifted Probabilistic Inference, 16. MIT Press, Cambridge, MA, 2020. In press.
Stochastic Planning and Lifted Inference [link] chapter   link   bibtex   7 downloads  
  2019 (11)
Deep Language-based Critiquing for Recommender Systems. Wu, G., Luo, K., Sanner, S., & Soh, H. In Proceedings of the 13th ACM Conference on Recommender Systems (RecSys-19), Copenhagen, Denmark, 2019.
Deep Language-based Critiquing for Recommender Systems [pdf] paper   Deep Language-based Critiquing for Recommender Systems [pdf] appendix   link   bibtex   70 downloads  
Reward Potentials for Planning with Learned Neural Network Transition Models. Say, B., Sanner, S., & Thiebaux, S. In Proceedings of the 25th International Conference on Principles and Practice of Constraint Programming (CP-19), Stamford, USA, 2019.
Reward Potentials for Planning with Learned Neural Network Transition Models [pdf] paper   link   bibtex   11 downloads  
Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning. Gimelfarb, M., Sanner, S., & Lee, C. In Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI-19), Tel Aviv, Israel, 2019.
Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning [pdf] paper   link   bibtex   6 downloads  
Deep Reactive Policies for Planning in Stochastic Nonlinear Domains. Bueno, T., de Barros, L. N., Maua, D., & Sanner, S. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, USA, 2019.
Deep Reactive Policies for Planning in Stochastic Nonlinear Domains [pdf] paper   link   bibtex   26 downloads  
Noise Contrastive Estimation for One-Class Collaborative Filtering. Wu, G., Volkovs, M., Soon, C. L., Sanner, S., & Rai, H. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-19), Paris, France, 2019.
Noise Contrastive Estimation for One-Class Collaborative Filtering [pdf] paper   link   bibtex   41 downloads  
One-Class Collaborative Filtering with the Queryable Variational Autoencoder. Wu, G., Bouadjenek, M. R., & Sanner, S. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-19), Paris, France, 2019.
One-Class Collaborative Filtering with the Queryable Variational Autoencoder [pdf] paper   One-Class Collaborative Filtering with the Queryable Variational Autoencoder [pdf] appendix   link   bibtex   23 downloads  
Metric Hybrid Factored Planning in Nonlinear Domains with Constraint Generation. Say, B., & Sanner, S. In Proceedings of the 16th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-19), Thessaloniki, Greece, 2019.
Metric Hybrid Factored Planning in Nonlinear Domains with Constraint Generation [pdf] paper   link   bibtex   15 downloads  
A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification. Wang, Y., Wu, G., Bouadjenek, M. R., Sanner, S., Su, S., & Zhang, Z. In Proceedings of the SIAM International Conference on Data Mining (SDM-19), Calgary, Canada, 2019.
A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification [pdf] paper   link   bibtex   15 downloads  
Bayesian Networks for Data Integration in the Absence of Foreign Keys. Zhang, B., Sanner, S., Bouadjenek, M. R., & Gupta, S. IEEE Transactions on Knowledge and Data Engineering (TKDE), 32(4): 803–808. 2019.
Bayesian Networks for Data Integration in the Absence of Foreign Keys [pdf] paper   Bayesian Networks for Data Integration in the Absence of Foreign Keys [pdf] appendix   link   bibtex   19 downloads  
Comparison of machine learning models for occupancy prediction in residential buildings using connected thermostat data. Huchuk, B., Sanner, S., & O'Brien, W. Building and Environment, 160: 106177. August 2019.
Comparison of machine learning models for occupancy prediction in residential buildings using connected thermostat data [link] paper   link   bibtex   11 downloads  
Evaluation of Machine Learning Algorithms for Predicting Readmission After Acute Myocardial Infarction Using Routinely Collected Clinical Data. Gupta, S., Ko, D. T., Azizi, P., Bouadjenek, M. R., Koh, M., Chong, A., Austin, P. C., & Sanner, S. Canadian Journal of Cardiology, 36: 878–885. June 2019.
Evaluation of Machine Learning Algorithms for Predicting Readmission After Acute Myocardial Infarction Using Routinely Collected Clinical Data [link] paper   link   bibtex   7 downloads  
  2018 (10)
Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach. Gimelfarb, M., Sanner, S., & Lee, C. In Proceedings of the 32nd Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-18), Montreal, QC, Canada, 2018.
Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach [pdf] paper   link   bibtex   16 downloads  
Two-stage Model for Automatic Playlist Continuation at Scale. Volkovs, M., Rai, H., Cheng, Z., Wu, G., Lu, Y., & Sanner, S. In Proceedings of the ACM Recommender Systems Challenge 2018 (RecSys-18), Vancouver, BC, Canada, 2018. 1st place in 2018 ACM RecSys Challenge.
Two-stage Model for Automatic Playlist Continuation at Scale [pdf] paper   link   bibtex   6 downloads  
Aesthetic Features for Personalized Photo Recommendation. Zhou, Y. Q., Wu, G., Sanner, S., & Manggala, P. In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys-18), Vancouver, BC, Canada, 2018.
Aesthetic Features for Personalized Photo Recommendation [pdf] paper   link   bibtex   7 downloads  
Collaborative Filtering with Behavioral Models. Sovilj, D., Sanner, S., Soh, H., & Li, H. In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (UMAP-18), Singapore, 2018.
Collaborative Filtering with Behavioral Models [pdf] paper   link   bibtex   8 downloads  
Symbolic Bucket Elimination for Piecewise Continuous Constrained Optimization. Ye, Z., Say, B., & Sanner, S. In Proceedings of the 15th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR-18), Delft, Netherlands, 2018. Recipient of the Best Student Paper Award.
Symbolic Bucket Elimination for Piecewise Continuous Constrained Optimization [pdf] paper   link   bibtex   18 downloads  
Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models. Say, B., & Sanner, S. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), Stockholm, Sweden, 2018.
Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models [pdf] paper   link   bibtex   11 downloads  
Efficient Symbolic Integration for Probabilistic Inference. Kolb, S., Mladenov, M., Sanner, S., Belle, V., & Kersting, K. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), Stockholm, Sweden, 2018.
Efficient Symbolic Integration for Probabilistic Inference [pdf] paper   link   bibtex   7 downloads  
A Longitudinal Study of Thermostat Behaviors based on Climate, Seasonal, and Energy Price Considerations using Connected Thermostat Data. Huchuk, B., O'Brien, W., & Sanner, S. Building and Environment, 139: 199–210. July 2018.
A Longitudinal Study of Thermostat Behaviors based on Climate, Seasonal, and Energy Price Considerations using Connected Thermostat Data [link] paper   link   bibtex   4 downloads  
Measuring and Mitigating the Costs of Attentional Switches in Active Network Monitoring for Cybersecurity. Kortschot, S. W., Sovilj, D., Jamieson, G. A., Sanner, S., Carrasco, C., & Soh, H. Human Factors. 2018.
Measuring and Mitigating the Costs of Attentional Switches in Active Network Monitoring for Cybersecurity [link] paper   link   bibtex   6 downloads  
Deep Learning with Microfluidics for Biotechnology. Riordon, J., Sovilj, D., Sanner, S., Sinton, D., & Young, E. Trends in Biotechnology. 2018.
Deep Learning with Microfluidics for Biotechnology [link] paper   link   bibtex   1 download  
  2017 (11)
Scalable Planning with Tensorflow for Hybrid Nonlinear Domains. Wu, G., Say, B., & Sanner, S. In Proceedings of the 31st Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-17), Long Beach, CA, 2017.
Scalable Planning with Tensorflow for Hybrid Nonlinear Domains [pdf] paper   link   bibtex   31 downloads  
Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming. Say, B., Wu, G., Zhou, Y. I., & Sanner, S. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne, Australia, 2017.
Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming [pdf] paper   link   bibtex   16 downloads  
A Longitudinal Study of Topic Classification on Twitter. Iman, Z., Sanner, S., Bouadjenek, M. R., & Xie, L. In Proceedings of the 11th International AAAI Conference on Web and Social Media (ICWSM-17), Montreal, Canada, 2017.
A Longitudinal Study of Topic Classification on Twitter [pdf] paper   link   bibtex   6 downloads  
Analytic Decision Analysis via Symbolic Dynamic Programming for Parameterized Hybrid MDPs. Kinathil, S., Soh, H., & Sanner, S. In Proceedings of the 27th Conference on Automated Planning and Scheduling (ICAPS-17), Pittsburgh, PA, 2017.
Analytic Decision Analysis via Symbolic Dynamic Programming for Parameterized Hybrid MDPs [pdf] paper   link   bibtex   16 downloads  
Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity. Rizoiu, M., Xie, L., Sanner, S., Cebrian, M., Yu, H., & Van Hentenryck, P. In Proceedings of the 26th International Conference on the World Wide Web (WWW-17), Perth, Australia, 2017.
Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity [pdf] paper   link   bibtex   6 downloads  
Deep Sequential Recommendation for Personalized Adaptive User Interfaces. Soh, H., Sanner, S., White, M., & Jamieson, G. In Proceedings of the 22nd ACM International Conference on Intelligent User Interfaces (IUI-17), Limassol, Cyprus, 2017.
Deep Sequential Recommendation for Personalized Adaptive User Interfaces [pdf] paper   link   bibtex   4 downloads  
Hindsight Optimization for Hybrid State and Action MDPs. Raghavan, A., Sanner, S., Tadepalli, P., Fern, A., & Khardon, R. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, USA, 2017.
Hindsight Optimization for Hybrid State and Action MDPs [pdf] paper   link   bibtex   15 downloads  
Low-rank Linear Cold-Start Recommendation from Social Data. Sedhain, S., Menon, A., Sanner, S., Xie, L., & Braziunas, D. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, USA, 2017.
Low-rank Linear Cold-Start Recommendation from Social Data [pdf] paper   link   bibtex   11 downloads  
Non-Markovian Rewards Expressed in LTL: Guiding Search Via Reward Shaping. Camacho, A., Chen, O., Sanner, S., & McIlraith, S. A. In Proceedings of the Tenth International Symposium on Combinatorial Search (SoCS-17), pages 159–160, 2017.
Non-Markovian Rewards Expressed in LTL: Guiding Search Via Reward Shaping [pdf] paper   link   bibtex   7 downloads  
Decision-Making with Non-Markovian Rewards: From LTL to automata-based reward shaping. Camacho, A., Chen, O., Sanner, S., & McIlraith, S. A. In Proceedings of the Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM-17), pages 279-283, 2017. See also University of Toronto Technical Report CSRG-632
Decision-Making with Non-Markovian Rewards: From LTL to automata-based reward shaping [pdf] paper   link   bibtex   5 downloads  
Decision-Making with Non-Markovian Rewards: Guiding search via automata-based reward shaping. Camacho, A., Chen, O., Sanner, S., & McIlraith, S. A. Technical Report CSRG-632, Department of Computer Science, University of Toronto, June 2017.
Decision-Making with Non-Markovian Rewards: Guiding search via automata-based reward shaping [pdf] paper   link   bibtex   14 downloads  
  2016 (7)
Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling, ICAPS 2016, London, UK, June 12-17, 2016. Coles, A. J., Coles, A., Edelkamp, S., Magazzeni, D., & Sanner, S., editors. AAAI Press. 2016.
link   bibtex  
Real-time Dynamic Programming for Markov Decision Processes with Imprecise Probabilities. Delgado, K. V., de Barros, L. N., Dias, D. B., & Sanner, S. Artificial Intelligence Journal (AIJ), 230: 192–223. 2016.
Real-time Dynamic Programming for Markov Decision Processes with Imprecise Probabilities [link] paper   link   bibtex   1 download  
A Non-homogenous Time Mixed Integer LP Formulation for Traffic Signal Control. Guilliard, I., Sanner, S., Trevizan, F., & Williams, B. Transport Research Record (TRR): Journal of the Transport Research Board, 2525. 2016. Recipient of the Kikuchi-Karlaftis Best Paper Award.
A Non-homogenous Time Mixed Integer LP Formulation for Traffic Signal Control [pdf] paper   link   bibtex   7 downloads  
Practical Linear Models for Large-Scale One-Class Collaborative Filtering. Sedhain, S., Bui, H., Kawale, J., Vlassis, N., Kveton, B., Menon, A., Bui, T., & Sanner, S. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), New York, USA, 2016.
Practical Linear Models for Large-Scale One-Class Collaborative Filtering [pdf] paper   link   bibtex   14 downloads  
A Symbolic Closed-form Solution to Sequential Market Making with Inventory. Kinathil, S., Sanner, S., Das, S., & Della-Penna, N. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), New York, USA, 2016.
A Symbolic Closed-form Solution to Sequential Market Making with Inventory [pdf] paper   link   bibtex   3 downloads  
Closed-form Gibbs Sampling for Graphical Models with Algebraic Constraints. Afshar, H., Sanner, S., & Webers, C. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, USA, 2016.
Closed-form Gibbs Sampling for Graphical Models with Algebraic Constraints [pdf] paper   link   bibtex   8 downloads  
On the Effectiveness of Linear Models for One-Class Collaborative Filtering. Sedhain, S., Menon, A., Sanner, S., & Braziunas, D. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, USA, 2016.
On the Effectiveness of Linear Models for One-Class Collaborative Filtering [pdf] paper   link   bibtex   7 downloads  
  2015 (10)
The 2014 International Planning Competition: Progress and Trends. Vallati, M., Chrpa, L., Grzes, M., McCluskey, T. L., Roberts, M., & Sanner, S. Artificial Intelligence Magazine (AI Magazine), 36(3): 90–98. 2015.
The 2014 International Planning Competition: Progress and Trends [pdf] paper   link   bibtex   3 downloads  
AutoRec: Autoencoders Meet Collaborative Filtering. Sedhain, S., Menon, A., Sanner, S., & Xie, L. In Proceedings of the 24th International Conference on the World Wide Web (WWW-15), Florence, Italy, 2015.
AutoRec: Autoencoders Meet Collaborative Filtering [pdf] paper   link   bibtex   7 downloads  
The Lifecyle of a Youtube Video: Phases, Content and Popularity. Yu, H., Xie, L., & Sanner, S. In Proceedings of the 9th International Conference on Web and Social Media (ICWSM-15), Oxford, UK, 2015.
The Lifecyle of a Youtube Video: Phases, Content and Popularity [pdf] paper   link   bibtex   4 downloads  
Linear-time Gibbs Sampling in Piecewise Graphical Models. Afshar, H., Sanner, S., & Abbasnejad, E. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, 2015.
Linear-time Gibbs Sampling in Piecewise Graphical Models [pdf] paper   link   bibtex   5 downloads  
Loss-calibrated Monte Carlo Action Selection. Abbasnejad, E., Domke, J., & Sanner, S. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, 2015.
Loss-calibrated Monte Carlo Action Selection [pdf] paper   link   bibtex   3 downloads  
Real-time Symbolic Dynamic Programming for Hybrid MDPs. Vianna, L. G. R., de Barros, L. N., & Sanner, S. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, 2015.
Real-time Symbolic Dynamic Programming for Hybrid MDPs [pdf] paper   link   bibtex   1 download  
Bayesian Model Averaging Naive Bayes: Averaging over an Exponential Number of Feature Models in Linear Time. Wu, G., Sanner, S., & Oliveira, R. F. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, 2015.
Bayesian Model Averaging Naive Bayes: Averaging over an Exponential Number of Feature Models in Linear Time [pdf] paper   link   bibtex   16 downloads  
On Term Selection Techniques for Patent Prior Art Search. Far, M. G., Sanner, S., Bouadjenek, M. R., Ferraro, G., & Hawking, D. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-15), pages 803–806, Santiago, Chile, 2015.
On Term Selection Techniques for Patent Prior Art Search [pdf] paper   link   bibtex   2 downloads  
A Study of Query Reformulation for Patent Prior Art Search with Partial Patent Applications. Bouadjenek, M. R., Sanner, S., & Ferraro, G. In Proceedings of the 15th International Conference on Artificial Intelligence and Law (ICAIL-15), pages 23–32, San Diego, USA, 2015.
A Study of Query Reformulation for Patent Prior Art Search with Partial Patent Applications [pdf] paper   link   bibtex   2 downloads  
Context-Aware Detection of Sneaky Vandalism on Wikipedia Across Multiple Languages. Tran, K., Christen, P., Sanner, S., & Xie, L. In Advances in Knowledge Discovery and Data Mining - 19th Pacific-Asia Conference (PAKDD-15), pages 380–391, Ho Chi Minh City, Vietnam, 2015. Recipient of the Best Student Paper Award.
Context-Aware Detection of Sneaky Vandalism on Wikipedia Across Multiple Languages [pdf] paper   link   bibtex   3 downloads  
  2014 (5)
Social Collaborative Filtering for Cold-start Recommendations. Sedhain, S., Sanner, S., Braziunas, D., Xie, L., & Christensen, J. In Proceedings of the 8th ACM Conference on Recommender Systems (RecSys-14), Foster City, USA, 2014.
Social Collaborative Filtering for Cold-start Recommendations [pdf] paper   link   bibtex   3 downloads  
Twitter-driven Youtube Views: Beyond Individual Influencers. Yu, H., Xie, L., & Sanner, S. In Proceedings of the 22nd ACM International Conference on Multimedia (ACM MM-14), Orlando, USA, 2014.
Twitter-driven Youtube Views: Beyond Individual Influencers [pdf] paper   link   bibtex  
Sequential Bayesian Optimisation for Spatial-Temporal Monitoring. Marchant, R., Ramos, F., & Sanner, S. In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI-14), Quebec City, Canada, 2014.
Sequential Bayesian Optimisation for Spatial-Temporal Monitoring [pdf] paper   link   bibtex   1 download  
Closed-form Solutions to a Subclass of Continuous Stochastic Games via Symbolic Dynamic Programming. Kinathil, S., Sanner, S., & Penna, N. D. In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI-14), Quebec City, Canada, 2014.
Closed-form Solutions to a Subclass of Continuous Stochastic Games via Symbolic Dynamic Programming [pdf] paper   link   bibtex   2 downloads  
Preference Learning (Dagstuhl Seminar 14101). Fürnkranz, J., Hüllermeier, E., Rudin, C., Slowinski, R., & Sanner, S. Dagstuhl Reports, 4(3): 1–27. 2014.
Preference Learning (Dagstuhl Seminar 14101) [pdf]Paper   doi   link   bibtex   1 download  
  2013 (6)
Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPs. Vianna, L. G. R., Sanner, S., & de Barros, L. N. In Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (UAI-13), Bellevue, USA, 2013.
Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPs [pdf] paper   link   bibtex   7 downloads  
Algorithms for Direct 0-1 Loss Optimization in Binary Classification. Nguyen, T., & Sanner, S. In Proceedings of the 30th International Conference on Machine Learning (ICML-13), Atlanta, USA, 2013.
Algorithms for Direct 0-1 Loss Optimization in Binary Classification [pdf] paper   link   bibtex   5 downloads  
Improving LDA Topic Models for Microblogs via Automatic Tweet Labeling and Pooling. Mehrotra, R., Sanner, S., Buntine, W., & Xie, L. In Proceedings of the 36th Annual ACM SIG Information Retrieval Conference (SIGIR-13), Dublin, Ireland, 2013.
Improving LDA Topic Models for Microblogs via Automatic Tweet Labeling and Pooling [pdf] paper   link   bibtex   10 downloads  
Learning Community-based Preferences via Dirichlet Process Mixtures of Gaussian Processes. Abbasnejad, E., Sanner, S., Bonilla, E. V., & Poupart, P. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-13), Beijing, China, 2013.
Learning Community-based Preferences via Dirichlet Process Mixtures of Gaussian Processes [pdf] paper   link   bibtex   1 download  
Robust Optimization for Hybrid MDPs with State-dependent Noise. Zamani, Z., Sanner, S., Delgado, K. V., & de Barros , L. N. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-13), Beijing, China, 2013.
Robust Optimization for Hybrid MDPs with State-dependent Noise [pdf] paper   link   bibtex   1 download  
Social Affinity Filtering: Recommendation through Fine-grained Analysis of User Interactions and Activities. Sedhain, S., Sanner, S., Xie, L., Kidd, R., Tran, K., & Christen, P. In Proceedings of the ACM Conference on Online Social Networks (COSN-13), Boston, USA, 2013.
Social Affinity Filtering: Recommendation through Fine-grained Analysis of User Interactions and Activities [pdf] paper   link   bibtex   7 downloads  
  2012 (8)
Symbolic Dynamic Programming for Continuous State and Observation POMDPs. Zamani, Z., Sanner, S., Poupart, P., & Kersting, K. In Proceedings of the 26th Annual Conference on Advances in Neural Information Processing Systems (NeurIPS-12), Lake Tahoe, Nevada, 2012.
Symbolic Dynamic Programming for Continuous State and Observation POMDPs [pdf] paper   link   bibtex   1 download  
Score-based Bayesian Skill Learning. Guo, S., Sanner, S., Graepel, T., & Buntine, W. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-12), Bristol, UK, 2012.
Score-based Bayesian Skill Learning [pdf] paper   link   bibtex   1 download  
Symbolic Variable Elimination for Discrete and Continuous Graphical Models. Sanner, S., & Abbasnejad, E. In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, 2012.
Symbolic Variable Elimination for Discrete and Continuous Graphical Models [pdf] paper   link   bibtex   4 downloads  
Symbolic Dynamic Programming for Continuous State and Action MDPs. Zamani, Z., Sanner, S., & Fang, C. In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, 2012.
Symbolic Dynamic Programming for Continuous State and Action MDPs [pdf] paper   link   bibtex   13 downloads  
On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off. Lim, K., Sanner, S., & Guo, S. In Proceedings of the 35th Annual ACM SIG Information Retrieval Conference (SIGIR-12), Portland, USA, 2012.
On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off [pdf] paper   link   bibtex   8 downloads  
New Objectives for Social Collaborative Filtering. Noel, J., Sanner, S., Tran, K., Christen, P., Xie, L., Bonilla, E., Abbasnejad, E., & Penna, N. D. In Proceedings of the 21st International Conference on the World Wide Web (WWW-12), Lyon, France, 2012.
New Objectives for Social Collaborative Filtering [pdf] paper   link   bibtex   37 downloads  
Proceedings of the 9th European Workshop on Reinforcement Learning (EWRL) 2011, Athens, Greece, September 9-11, 2011. Sanner, S., & Hutter, M., editors. Volume 7188, of Lecture Notes in Computer Science.Springer. 2012.
Proceedings of the 9th European Workshop on Reinforcement Learning (EWRL) 2011, Athens, Greece, September 9-11, 2011 [pdf] paper   link   bibtex  
A Survey of the Seventh International Planning Competition. Coles, A., Coles, A., Olaya, A. G., Jiménez, S., López, C. L., Sanner, S., & Yoon, S. Artificial Intelligence Magazine (AI Magazine), 33(1): 83–88. 2012.
A Survey of the Seventh International Planning Competition [pdf] paper   link   bibtex   1 download  
  2011 (6)
Diverse Retrieval via Greedy Optimization of Expected 1-call@k in a Latent Subtopic Relevance Model. Sanner, S., Guo, S., Graepel, T., Kharazmi, S., & Karimi, S. In 20th ACM Conference on Information and Knowledge Management (CIKM-11), Glasgow, UK, 2011.
Diverse Retrieval via Greedy Optimization of Expected 1-call@k in a Latent Subtopic Relevance Model [pdf] paper   link   bibtex   16 downloads  
Symbolic Dynamic Programming for Discrete and Continuous State MDPs. Sanner, S., Delgado, K. V., & de Barros , L. N. In Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence (UAI-11), Barcelona, Spain, 2011.
Symbolic Dynamic Programming for Discrete and Continuous State MDPs [pdf] paper   link   bibtex   7 downloads  
Sparse Kernel-SARSA(lambda) with an Eligibility Trace. Robards, M., Sunehag, P., Sanner, S., & Marthi, B. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-11), 2011.
Sparse Kernel-SARSA(lambda) with an Eligibility Trace [pdf] paper   link   bibtex   2 downloads  
Multi-Evidence Lifted Message Passing with Application to PageRank and the Kalman Filter. Ahmadi, B., Kersting, K., & Sanner, S. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI-11), 2011.
Multi-Evidence Lifted Message Passing with Application to PageRank and the Kalman Filter [pdf] paper   link   bibtex  
Efficient Solutions to Factored MDPs with Imprecise Transition Probabilities. Delgado, K. V., Sanner, S., & de Barros , L. N. Artificial Intelligence Journal (AIJ), 175: 1498–1527. 2011.
Efficient Solutions to Factored MDPs with Imprecise Transition Probabilities [pdf] paper   link   bibtex  
Using Mathematical Programming to Solve Factored Markov Decision Processes with Imprecise Probabilities. Delgado, K. V., de Barros , L. N., Cozman, F. G., & Sanner, S. International Journal of Approximate Reasoning (IJAR), 52(7): 1000–1017. 2011.
Using Mathematical Programming to Solve Factored Markov Decision Processes with Imprecise Probabilities [pdf] paper   link   bibtex  
  2010 (8)
Relational Dynamic Influence Diagram Language (RDDL): Language Description — http://users.cecs.anu.edu.au/ ssanner/IPPC_2011/RDDL.pdf. Sanner, S. 2010. Unpublished Manuscript, Australian National University
Relational Dynamic Influence Diagram Language (RDDL): Language Description — http://users.cecs.anu.edu.au/ ssanner/IPPC_2011/RDDL.pdf [pdf]Paper   link   bibtex   3 downloads  
Gaussian Process Preference Elicitation. Bonilla, E., Guo, S., & Sanner, S. In Advances in Neural Information Processing Systems 24 (NeurIPS-10), Vancouver, Canada, 2010. MIT Press
Gaussian Process Preference Elicitation [pdf] paper   link   bibtex   5 downloads  
Symbolic Dynamic Programming for First-order POMDPs. Sanner, S., & Kersting, K. In Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI-10), Atlanta, Georgia, July 19-23 2010. AAAI Press
Symbolic Dynamic Programming for First-order POMDPs [pdf] paper   link   bibtex   5 downloads  
Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda. Downey, C., & Sanner, S. In Proceedings of the 27th International Conference on Machine Learning (ICML-10), Haifa, Israel, June 21-24 2010.
Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda [pdf] paper   link   bibtex   3 downloads  
Probabilistic Latent Maximal Marginal Relevance. Guo, S., & Sanner, S. In Proceedings of the 33rd Annual ACM SIG Information Retrieval Conference (SIGIR-10), Geneva, Switzerland, July 11-15 2010. ACM
Probabilistic Latent Maximal Marginal Relevance [pdf] paper   link   bibtex  
Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries. Guo, S., & Sanner, S. 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.
Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries [pdf] paper   link   bibtex   33 downloads  
Approximate Dynamic Programming with Affine ADDs. Sanner, S., Uther, W., & Delgado, K. V. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-10), Toronto, Canada, 2010.
Approximate Dynamic Programming with Affine ADDs [pdf] paper   link   bibtex   3 downloads  
Symbolic dynamic programming. Sanner, S., & Kersting, K. In Encyclopedia of Machine Learning, pages 946–954. Springer-Verlag, 2010.
Symbolic dynamic programming [pdf] paper   link   bibtex  
  2009 (3)
Efficient Solutions to Factored MDPs with Imprecise Transition Probabilities. Delgado, K. V., Sanner, S., de Barros, L. N., & Cozman, F. G. In Proceedings of the 19th Conference on Automated Planning and Scheduling (ICAPS-09), 2009.
Efficient Solutions to Factored MDPs with Imprecise Transition Probabilities [pdf] paper   link   bibtex   1 download  
Bayesian Real-time Dynamic Programming. Sanner, S., Goetschalckx, R., Driessens, K., & Shani, G. In Boutilier, editor(s), 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pages 1–8, Pasadena, USA, July 2009.
Bayesian Real-time Dynamic Programming [pdf] paper   link   bibtex   8 downloads  
Practical Solution Techniques for First-order MDPs. Sanner, S., & Boutilier, C. Artificial Intelligence Journal (AIJ),748-788. April 2009. Recipient of the 2014 Artificial Intelligence Journal (AIJ) Prominent Paper Award.
Practical Solution Techniques for First-order MDPs [pdf] paper   link   bibtex   21 downloads  
  2008 (4)
Reinforcement learning with the use of costly features. Goetschalckx, R., Sanner, S., & Driessens, K. Lecture Notes in Computer Science, 5323: 124–135. November 2008.
Reinforcement learning with the use of costly features [link]Paper   Reinforcement learning with the use of costly features [pdf] paper   doi   link   bibtex   1 download  
Cost-sensitive parsimonious linear regression. Goetschalckx, R., Sanner, S., & Driessens, K. In Proceedings of the 8th IEEE International Conference on Data Mining (ICDM-08), pages 809–814, 2008. IEEE Computer Society
Cost-sensitive parsimonious linear regression [link]Paper   Cost-sensitive parsimonious linear regression [pdf] paper   doi   link   bibtex  
Reinforcement Learning with the Use of Costly Features. Goetschalckx, R., Sanner, S., & Driessens, K. In European Conference on Artificial Intelligence (ECAI-08), 2008.
Reinforcement Learning with the Use of Costly Features [pdf] paper   link   bibtex   1 download  
First-order Decision-theoretic Planning in Structured Relational Environments. Sanner, S. Ph.D. Thesis, University of Toronto, Toronto, ON, Canada, March 2008.
First-order Decision-theoretic Planning in Structured Relational Environments [pdf] paper   link   bibtex   10 downloads  
  2007 (2)
Approximate solution techniques for factored first-order MDPs. Sanner, S., & Boutilier, C. In Proceedings of the 17th Conference on Automated Planning and Scheduling (ICAPS-07), 2007.
Approximate solution techniques for factored first-order MDPs [pdf] paper   link   bibtex   1 download  
Learning CRFs with hierarchical features: An application to the game of Go. Sanner, S., Graepel, T., Herbrich, R., & Minka, T. In Proceedings of the Workshop on Constrained Optimization and Structured Output Spaces (WCSOS-07), 2007.
Learning CRFs with hierarchical features: An application to the game of Go [pdf] paper   link   bibtex   4 downloads  
  2006 (3)
Practical linear value-approximation techniques for first-order MDPs. Sanner, S., & Boutilier, C. In Proceedings of the 22nd Conference on Uncertainty in AI (UAI-06), 2006.
Practical linear value-approximation techniques for first-order MDPs [pdf] paper   link   bibtex   1 download  
An ordered theory resolution calculus for hybrid reasoning in first-order extensions of description logic. Sanner, S., & McIlraith, S. In Proceedings of the 10th International Conference on Principles of Knowledge Representation and Reasoning (KR-06), 2006.
An ordered theory resolution calculus for hybrid reasoning in first-order extensions of description logic [pdf] paper   link   bibtex   13 downloads  
Online feature discovery in relational reinforcement learning. Sanner, S. In Proceedings of the Open Problems in Statistical Relational Learning Workshop (SRL-06), 2006.
Online feature discovery in relational reinforcement learning [pdf] paper   link   bibtex   2 downloads  
  2005 (4)
Affine algebraic decision diagrams (AADDs) and their application to structured probabilistic inference. Sanner, S., & McAllester, D. In Proceedings of the 19th International Joint Conference on AI (IJCAI-05), 2005.
Affine algebraic decision diagrams (AADDs) and their application to structured probabilistic inference [pdf] paper   link   bibtex   3 downloads  
Approximate linear programming for first-order MDPs. Sanner, S., & Boutilier, C. In Proceedings of the 21st Conference on Uncertainty in AI (UAI-05), 2005.
Approximate linear programming for first-order MDPs [pdf] paper   link   bibtex   2 downloads  
Simultaneous learning of structure and value in relational reinforcement learning. Sanner, S. In Proceedings of the Rich Representations for Relational Reinforcement Learning Workshop (RRfRL-05), 2005.
Simultaneous learning of structure and value in relational reinforcement learning [pdf] paper   link   bibtex   2 downloads  
Future directions for first-order decision-theoretic planning. Sanner, S. Technical Report University of Toronto, 2005.
Future directions for first-order decision-theoretic planning [pdf] paper   link   bibtex   1 download  
  2004 (2)
Relational and first-order decision-theoretic planning: Foundations and future directions. Sanner, S. Technical Report University of Toronto, 2004.
Relational and first-order decision-theoretic planning: Foundations and future directions [pdf] paper   link   bibtex   20 downloads  
Refutation-complete binary decision diagrams. Sanner, S. Technical Report University of Toronto, 2004.
Refutation-complete binary decision diagrams [pdf] paper   link   bibtex   4 downloads  
  2003 (1)
Towards practical taxonomic classification for description logics on the Semantic Web. Sanner, S. Technical Report KSL-03-06, Stanford University, Knowledge Systems Lab, 2003.
Towards practical taxonomic classification for description logics on the Semantic Web [pdf] paper   link   bibtex   5 downloads  
  2002 (2)
Learning hierarchical object maps of non-stationary environments with mobile robots. Anguelov, D., Biswas, R., Koller, D., Limketkai, B., Sanner, S., & Thrun, S. In Proceedings of the 18th Conference on Uncertainty in AI (UAI-02), 2002.
Learning hierarchical object maps of non-stationary environments with mobile robots [pdf] paper   link   bibtex   2 downloads  
Towards object mapping in dynamic environments with mobile robots. Biswas, R., Limketkai, B., Sanner, S., & Thrun, S. In Proceedings of the Conference on Intelligent Robots and Systems (IROS-02), 2002.
Towards object mapping in dynamic environments with mobile robots [pdf] paper   link   bibtex  
  2000 (1)
Achieving efficient and cognitively plausible learning in backgammon. Sanner, S., Anderson, J. R., Lebiere, C., & Lovett, M. In Proceedings of the 17th International Conference on Machine Learning (ICML-00), 2000.
Achieving efficient and cognitively plausible learning in backgammon [pdf] paper   link   bibtex   5 downloads