Sihan Liu

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Daniel KaneUniversity of California, San DiegoPotvrđena adresa e-pošte na ucsd.edu
Ilias DiakonikolasUniversity of Wisconsin-MadisonPotvrđena adresa e-pošte na wisc.edu
Shachar LovettAssociate Professor of Computer Science, University of California San DiegoPotvrđena adresa e-pošte na eng.ucsd.edu
Gaurav MahajanPostdoctoral Associate, Yale UniversityPotvrđena adresa e-pošte na yale.edu
Vasilis KontonisUniversity of Texas at AustinPotvrđena adresa e-pošte na cs.utexas.edu
Max HopkinsPrinceton UniversityPotvrđena adresa e-pošte na princeton.edu
Nikos ZarifisUniversity of Wisconsin-MadisonPotvrđena adresa e-pošte na wisc.edu
Csaba SzepesvariDeepMind & University of AlbertaPotvrđena adresa e-pošte na cs.ualberta.ca
Gellért WeiszDeepMind, UCL, gellert@google.comPotvrđena adresa e-pošte na google.com
Daniel BeagleholePhD Student, UCSDPotvrđena adresa e-pošte na ucsd.edu
Clément L. CanonneUniversity of SydneyPotvrđena adresa e-pošte na sydney.edu.au
Christos TzamosUniversity of Athens and University of Wisconsin-MadisonPotvrđena adresa e-pošte na di.uoa.gr
Christopher YeStudent, UC San DiegoPotvrđena adresa e-pošte na ucsd.edu
Russell ImpagliazzoUCSDPotvrđena adresa e-pošte na ucsd.edu

Prati

Sihan Liu

University of California San Diego

Potvrđena adresa e-pošte na ucsd.edu - Početna stranica

Theoretical Machine Learning Distribution Testing


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Computational-Statistical Gaps in Reinforcement Learning D Kane, S Liu, S Lovett, G Mahajan Conference on Learning Theory, 1282-1302, 2022	26	2022
Efficient testable learning of halfspaces with adversarial label noise I Diakonikolas, D Kane, V Kontonis, S Liu, N Zarifis Advances in Neural Information Processing Systems 36, 2024	12	2024
Sampling Equilibria: Fast No-Regret Learning in Structured Games D Beaglehole, M Hopkins, D Kane, S Liu, S Lovett Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2023	10	2023
Near-Optimal Bounds for Testing Histogram Distributions CL Canonne, I Diakonikolas, DM Kane, S Liu Advances in Neural Information Processing Systems, 2022, 2022	7	2022
Exponential hardness of reinforcement learning with linear function approximation S Liu, G Mahajan, D Kane, S Lovett, G Weisz, C Szepesvári The Thirty Sixth Annual Conference on Learning Theory, 1588-1617, 2023	6*	2023
Replicability in High Dimensional Statistics M Hopkins, R Impagliazzo, D Kane, S Liu, C Ye arXiv preprint arXiv:2406.02628, 2024	4*	2024
Online Robust Mean Estimation DM Kane, I Diakonikolas, H Xiao, S Liu Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2024	4	2024
Convergence and sample complexity of SGD in GANs V Kontonis, S Liu, C Tzamos arXiv preprint arXiv:2012.00732, 2020	4	2020
Super Non-singular Decompositions of Polynomials and Their Application to Robustly Learning Low-Degree PTFs I Diakonikolas, DM Kane, V Kontonis, S Liu, N Zarifis Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 152-159, 2024	2	2024
Testing Closeness of Multivariate Distributions via Ramsey Theory I Diakonikolas, DM Kane, S Liu Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 340-347, 2024	2	2024
Improved classical shadows from local symmetries in the Schur basis D Grier, S Liu, G Mahajan arXiv preprint arXiv:2405.09525, 2024	1	2024
Replicable Uniformity Testing S Liu, C Ye arXiv preprint arXiv:2410.10892, 2024		2024
Testable Learning of General Halfspaces with Adversarial Label Noise I Diakonikolas, D Kane, S Liu, N Zarifis The Thirty Seventh Annual Conference on Learning Theory, 1308-1335, 2024		2024

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