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Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.

S. Garg, A. Setlur, Z. Lipton, S. Balakrishnan, V. Smith, and A. Raghunathan. CoRR, (2023)

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Covariate Distribution Aware Meta-learning.A. Setlur, S. Dingliwal, and B. Póczos. CoRR, (2020)Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.S. Garg, A. Setlur, Z. Lipton, S. Balakrishnan, V. Smith, and A. Raghunathan. CoRR, (2023)Multitask Learning Can Improve Worst-Group Outcomes.A. Kulkarni, L. Dery, A. Setlur, A. Raghunathan, A. Talwalkar, and G. Neubig. CoRR, (2023)Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts.A. Setlur, D. Dennis, B. Eysenbach, A. Raghunathan, C. Finn, V. Smith, and S. Levine. ICLR, OpenReview.net, (2023)Explaining The Efficacy of Counterfactually-Augmented Data.D. Kaushik, A. Setlur, E. Hovy, and Z. Lipton. CoRR, (2020)Explaining the Efficacy of Counterfactually Augmented Data.D. Kaushik, A. Setlur, E. Hovy, and Z. Lipton. ICLR, OpenReview.net, (2021)ReStGAN: A step towards visually guided shopper experience via text-to-image synthesis.S. Surya, A. Setlur, A. Biswas, and S. Negi. WACV, page 1189-1197. IEEE, (2020)Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts.A. Chen, Y. Lee, A. Setlur, S. Levine, and C. Finn. CoRR, (2023)Contextual Reliability: When Different Features Matter in Different Contexts.G. Ghosal, A. Setlur, D. Brown, A. Dragan, and A. Raghunathan. ICML, volume 202 of Proceedings of Machine Learning Research, page 11300-11320. PMLR, (2023)Robust Handwriting Recognition with Limited and Noisy Data.H. Pham, A. Setlur, S. Dingliwal, T. Lin, B. Póczos, K. Huang, Z. Li, J. Lim, C. McCormack, and T. Vu. ICFHR, page 301-306. IEEE, (2020)

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Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.

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Disambiguation of "Setlur, Amrith"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.

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Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.