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  2024 (2)
Interpretable Compositional Representations for Robust Few-Shot Generalization. Mishra, S.; Zhu, P.; and Saligrama, V. IEEE Trans. Pattern Anal. Mach. Intell., 46(3): 1496–1512. 2024.
Interpretable Compositional Representations for Robust Few-Shot Generalization [link]Paper   doi   link   bibtex  
SynCDR : Training Cross Domain Retrieval Models with Synthetic Data. Mishra, S.; Saenko, K.; and Saligrama, V. CoRR, abs/2401.00420. 2024.
SynCDR : Training Cross Domain Retrieval Models with Synthetic Data [link]Paper   doi   link   bibtex   1 download  
  2023 (10)
Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the "What" and Focus on the "How"!. Chen, C.; Walker, D.; and Saligrama, V. In Rogers, A.; Boyd-Graber, J. L.; and Okazaki, N., editor(s), Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2023, Toronto, Canada, July 9-14, 2023, pages 9529–9549, 2023. Association for Computational Linguistics
Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the "What" and Focus on the "How"! [link]Paper   doi   link   bibtex  
Fine-grained Few-shot Recognition by Deep Object Parsing. Zhu, R.; Zhu, P.; Mishra, S.; and Saligrama, V. In 34th British Machine Vision Conference 2023, BMVC 2023, Aberdeen, UK, November 20-24, 2023, pages 330–331, 2023. BMVA Press
Fine-grained Few-shot Recognition by Deep Object Parsing [link]Paper   link   bibtex  
Learning to Drive Anywhere. Zhu, R.; Huang, P.; Ohn-Bar, E.; and Saligrama, V. In Tan, J.; Toussaint, M.; and Darvish, K., editor(s), Conference on Robot Learning, CoRL 2023, 6-9 November 2023, Atlanta, GA, USA, volume 229, of Proceedings of Machine Learning Research, pages 3631–3653, 2023. PMLR
Learning to Drive Anywhere [link]Paper   link   bibtex  
Scaffolding a Student to Instill Knowledge. Kag, A.; Acar, D. A. E.; Gangrade, A.; and Saligrama, V. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023. OpenReview.net
Scaffolding a Student to Instill Knowledge [link]Paper   link   bibtex   1 download  
Efficient Edge Inference by Selective Query. Kag, A.; Fedorov, I.; Gangrade, A.; Whatmough, P. N.; and Saligrama, V. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023. OpenReview.net
Efficient Edge Inference by Selective Query [link]Paper   link   bibtex   1 download  
InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion. Lin, F.; Yue, Y.; Zhang, Z.; Hou, S.; Yamada, K. D.; Kolachalama, V.; and Saligrama, V. In Oh, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M.; and Levine, S., editor(s), Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023.
InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion [link]Paper   link   bibtex  
Learning Human Action Recognition Representations Without Real Humans. Zhong, H.; Mishra, S.; Kim, D.; Jin, S.; Panda, R.; Kuehne, H.; Karlinsky, L.; Saligrama, V.; Oliva, A.; and Feris, R. In Oh, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M.; and Levine, S., editor(s), Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023.
Learning Human Action Recognition Representations Without Real Humans [link]Paper   link   bibtex  
Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction. Chen, C.; Walker, D.; and Saligrama, V. CoRR, abs/2302.00239. 2023.
Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction [link]Paper   doi   link   bibtex   1 download  
Learning to Drive Anywhere. Zhu, R.; Huang, P.; Ohn-Bar, E.; and Saligrama, V. CoRR, abs/2309.12295. 2023.
Learning to Drive Anywhere [link]Paper   doi   link   bibtex  
Learning Human Action Recognition Representations Without Real Humans. Zhong, H.; Mishra, S.; Kim, D.; Jin, S.; Panda, R.; Kuehne, H.; Karlinsky, L.; Saligrama, V.; Oliva, A.; and Feris, R. CoRR, abs/2311.06231. 2023.
Learning Human Action Recognition Representations Without Real Humans [link]Paper   doi   link   bibtex  
  2022 (11)
Condensing CNNs with Partial Differential Equations. Kag, A.; and Saligrama, V. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, pages 600–609, 2022. IEEE
Condensing CNNs with Partial Differential Equations [link]Paper   doi   link   bibtex   1 download  
Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data. Mishra, S.; Panda, R.; Phoo, C. P.; Chen, C. R.; Karlinsky, L.; Saenko, K.; Saligrama, V.; and Feris, R. S. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, pages 9184–9194, 2022. IEEE
Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data [link]Paper   doi   link   bibtex   1 download  
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. Chen, T.; Gangrade, A.; and Saligrama, V. In Chaudhuri, K.; Jegelka, S.; Song, L.; Szepesvári, C.; Niu, G.; and Sabato, S., editor(s), International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, volume 162, of Proceedings of Machine Learning Research, pages 3123–3148, 2022. PMLR
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk [link]Paper   link   bibtex   4 downloads  
ActiveHedge: Hedge meets Active Learning. Kumar, B.; Abernethy, J. D.; and Saligrama, V. In Chaudhuri, K.; Jegelka, S.; Song, L.; Szepesvári, C.; Niu, G.; and Sabato, S., editor(s), International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, volume 162, of Proceedings of Machine Learning Research, pages 11694–11709, 2022. PMLR
ActiveHedge: Hedge meets Active Learning [link]Paper   link   bibtex  
Faster Algorithms for Learning Convex Functions. Siahkamari, A.; Acar, D. A. E.; Liao, C.; Geyer, K. L.; Saligrama, V.; and Kulis, B. In Chaudhuri, K.; Jegelka, S.; Song, L.; Szepesvári, C.; Niu, G.; and Sabato, S., editor(s), International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, volume 162, of Proceedings of Machine Learning Research, pages 20176–20194, 2022. PMLR
Faster Algorithms for Learning Convex Functions [link]Paper   link   bibtex  
How Transferable are Video Representations Based on Synthetic Data?. Kim, Y.; Mishra, S.; Jin, S.; Panda, R.; Kuehne, H.; Karlinsky, L.; Saligrama, V.; Saenko, K.; Oliva, A.; and Feris, R. In Koyejo, S.; Mohamed, S.; Agarwal, A.; Belgrave, D.; Cho, K.; and Oh, A., editor(s), Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022.
How Transferable are Video Representations Based on Synthetic Data? [link]Paper   link   bibtex  
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. Chen, T.; Gangrade, A.; and Saligrama, V. CoRR, abs/2204.00706. 2022.
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk [link]Paper   doi   link   bibtex   4 downloads  
Learning Compositional Representations for Effective Low-Shot Generalization. Mishra, S.; Zhu, P.; and Saligrama, V. CoRR, abs/2204.08090. 2022.
Learning Compositional Representations for Effective Low-Shot Generalization [link]Paper   doi   link   bibtex  
FedHeN: Federated Learning in Heterogeneous Networks. Acar, D. A. E.; and Saligrama, V. CoRR, abs/2207.03031. 2022.