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Dive into the research topics where Yuval Dagan is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Dimension-free Private Mean Estimation for Anisotropic Distributions
Dagan, Y., Jordan, M. I., Yang, X., Zakynthinou, L. & Zhivotovskiy, N., 2024, In: Advances in Neural Information Processing Systems. 37Research output: Contribution to journal › Conference article › peer-review
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From External to Swap Regret 2.0: An Efficient Reduction for Large Action Spaces
Dagan, Y., Daskalakis, C., Fishelson, M. & Golowich, N., 10 Jun 2024, STOC 2024 - Proceedings of the 56th Annual ACM Symposium on Theory of Computing. Mohar, B., Shinkar, I. & O�Donnell, R. (eds.). Association for Computing Machinery, p. 1216-1222 7 p. (Proceedings of the Annual ACM Symposium on Theory of Computing).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Maximizing utility in multi-agent environments by anticipating the behavior of other learners
Assos, A., Dagan, Y. & Daskalakis, C., 2024, In: Advances in Neural Information Processing Systems. 37Research output: Contribution to journal › Conference article › peer-review
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Ambient Diffusion: Learning Clean Distributions from Corrupted Data
Daras, G., Shah, K., Dagan, Y., Gollakota, A., Dimakis, A. G. & Klivans, A., 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent
Daras, G., Dagan, Y., Dimakis, A. G. & Daskalakis, C., 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review