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Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.

A. Chen, Y. Lee, A. Setlur, S. Levine, and C. Finn. CoRR, (2023)

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Covariate Distribution Aware Meta-learning.A. Setlur, S. Dingliwal, and B. Póczos. CoRR, (2020)Multitask Learning Can Improve Worst-Group Outcomes.A. Kulkarni, L. Dery, A. Setlur, A. Raghunathan, A. Talwalkar, and G. Neubig. CoRR, (2023)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)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)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)Towards Using Heterogeneous Relation Graphs for End-to-End TTS.A. Setlur, A. Madaan, T. Parekh, Y. Yang, and A. Black. ASRU, page 1162-1169. IEEE, (2021)

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Disambiguation of "Setlur, Amrith"

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Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.

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Disambiguation of "Setlur, Amrith"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.

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Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.