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Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss.

Y. Carmon, A. Jambulapati, Y. Jin, and A. Sidford. COLT, volume 134 of Proceedings of Machine Learning Research, page 866-882. PMLR, (2021)

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Yair Schiftan

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Information, Estimation, and Lookahead in the Gaussian channelK. Venkat, T. Weissman, Y. Carmon, and S. Shamai. CoRR, (2013)Lower Bounds for Non-Convex Stochastic Optimization.Y. Arjevani, Y. Carmon, J. Duchi, D. Foster, N. Srebro, and B. Woodworth. 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)Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.M. Wortsman, G. Ilharco, S. Gadre, R. Roelofs, R. Lopes, A. Morcos, H. Namkoong, A. Farhadi, Y. Carmon, S. Kornblith and 1 other author(s). ICML, volume 162 of Proceedings of Machine Learning Research, page 23965-23998. PMLR, (2022)Making SGD Parameter-Free.Y. Carmon, and O. Hinder. COLT, volume 178 of Proceedings of Machine Learning Research, page 2360-2389. PMLR, (2022)Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds.Y. Wald, G. Yona, U. Shalit, and Y. Carmon. ICLR, OpenReview.net, (2023)First-Order Methods for Nonconvex Quadratic Minimization.Y. Carmon, and J. Duchi. SIAM Rev., 62 (2): 395-436 (2020)A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions.Y. Carmon, A. Jambulapati, Y. Jin, and A. Sidford. CoRR, (2023)Variance Reduction for Matrix Games.Y. Carmon, Y. Jin, A. Sidford, and K. Tian. NeurIPS, page 11377-11388. (2019)Acceleration with a Ball Optimization Oracle.Y. Carmon, A. Jambulapati, Q. Jiang, Y. Jin, Y. Lee, A. Sidford, and K. Tian. NeurIPS, (2020)

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Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss.

Please choose a person to relate this publication to

Yair Schiftan

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Disambiguation of "Carmon, Yair"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss.

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Yair Schiftan

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Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss.