Adversarial Laws of Large Numbers and Optimal Regret in Online Classification-Reference-Cited by-同舟云学术

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Adversarial Laws of Large Numbers and Optimal Regret in Online Classification

Published:2023-11-03 Issue: Volume: Page:STOC21-154-STOC21-210
ISSN:0097-5397
Container-title:SIAM Journal on Computing
language:en
Short-container-title:SIAM J. Comput.

Author:

Alon Noga¹,Ben-Eliezer Omri²^ORCID,Dagan Yuval³,Moran Shay⁴,Naor Moni⁵,Yogev Eylon⁶

Affiliation:

1. Department of Mathematics, Princeton University, Princeton, NJ 08540 USA, and Schools of Mathematics and Computer Science, Tel Aviv University, 69978, Tel Aviv, Israel.

2. Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139 USA.

3. Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720 USA.

4. Departments of Mathematics and Computer Science, Technion, 32000, Haifa, Israel, and Google Research, Israel.

5. Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel.

6. Department of Computer Science, Bar Ilan University, Ramat Gan, 52900, Israel.

Funder

National Science Foundation

BSF

Israel Science Foundation

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

General Mathematics,General Computer Science

Reference36 articles.

1. Transversal numbers for hypergraphs arising in geometry

2. The Space Complexity of Approximating the Frequency Moments

3. Learnability and the Vapnik-Chervonenkis dimension

4. An analog of the minimax theorem for vector payoffs

5. Concentration inequalities for sampling without replacement

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