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Just train twice: Improving group robustness without training group information

E. Liu, B. Haghgoo, A. Chen, A. Raghunathan, P. Koh, S. Sagawa, P. Liang, and C. Finn. International Conference on Machine Learning, page 6781--6792. PMLR, (2021)

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Shiori Kubo

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Genotype Specification LanguageE. Wilson, S. Sagawa, J. Weis, M. Schubert, M. Bissell, B. Hawthorne, C. Reeves, J. Dean, and D. Platt. ACS Synth. Biol., 5 (6): 471--478 (Jun 17, 2016)Wilds: A benchmark of in-the-wild distribution shiftsP. Koh, S. Sagawa, H. Marklund, S. Xie, M. Zhang, A. Balsubramani, W. Hu, M. Yasunaga, R. Phillips, I. Gao and 1 other author(s). International Conference on Machine Learning, page 5637--5664. PMLR, (2021)OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.A. Awadalla, I. Gao, J. Gardner, J. Hessel, Y. Hanafy, W. Zhu, K. Marathe, Y. Bitton, S. Gadre, S. Sagawa and 6 other author(s). CoRR, (2023)WILDS: A Benchmark of in-the-Wild Distribution Shifts.P. Koh, S. Sagawa, H. Marklund, S. Xie, M. Zhang, A. Balsubramani, W. Hu, M. Yasunaga, R. Phillips, S. Beery and 6 other author(s). CoRR, (2020)Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.S. Sagawa, P. Koh, T. Hashimoto, and P. Liang. CoRR, (2019)Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization.J. Miller, R. Taori, A. Raghunathan, S. Sagawa, P. Koh, V. Shankar, P. Liang, Y. Carmon, and L. Schmidt. ICML, volume 139 of Proceedings of Machine Learning Research, page 7721-7735. PMLR, (2021)WILDS: A Benchmark of in-the-Wild Distribution Shifts.P. Koh, S. Sagawa, H. Marklund, S. Xie, M. Zhang, A. Balsubramani, W. Hu, M. Yasunaga, R. Phillips, I. Gao and 13 other author(s). ICML, volume 139 of Proceedings of Machine Learning Research, page 5637-5664. PMLR, (2021)Just Train Twice: Improving Group Robustness without Training Group Information.E. Liu, B. Haghgoo, A. Chen, A. Raghunathan, P. Koh, S. Sagawa, P. Liang, and C. Finn. ICML, volume 139 of Proceedings of Machine Learning Research, page 6781-6792. PMLR, (2021)Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalizationS. Sagawa, P. Koh, T. Hashimoto, and P. Liang. International Conference on Learning Representations (ICLR), (2020)Distributionally Robust Neural Networks.S. Sagawa, P. Koh, T. Hashimoto, and P. Liang. ICLR, OpenReview.net, (2020)

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Disambiguation of "Sagawa, Shiori"

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Just train twice: Improving group robustness without training group information

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Shiori Kubo

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Disambiguation of "Sagawa, Shiori"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Just train twice: Improving group robustness without training group information

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Shiori Kubo

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Just train twice: Improving group robustness without training group information