Chen-Yu Wei

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	Total	Desde 2019
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Índice i10	32	32

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Haipeng LuoAssociate Professor, University of Southern CaliforniaDirección de correo verificada de usc.edu
Chung-Wei LeeUniversity of Southern CaliforniaDirección de correo verificada de usc.edu
Julian ZimmertGoogle ResearchDirección de correo verificada de google.com
Mengxiao ZhangAssistant professor, University of IowaDirección de correo verificada de uiowa.edu
John LangfordMicrosoft Research New YorkDirección de correo verificada de hunch.net
Alekh AgarwalGoogleDirección de correo verificada de google.com
Christoph DannResearch Scientist, GoogleDirección de correo verificada de google.com
Chi-Jen LuResearch Fellow, Institute of Information Science, Academia SinicaDirección de correo verificada de iis.sinica.edu.tw
Rahul JainProfessor of ECE and CS, USC and visiting Research Scientist, Google DeepMindDirección de correo verificada de usc.edu
Mehdi Jafarnia JahromiDeepMindDirección de correo verificada de google.com
Weiqiang ZhengYale UniversityDirección de correo verificada de yale.edu
Yang CaiAssociate Professor of Computer Science and Economics, Yale UniversityDirección de correo verificada de yale.edu
Kaiqing ZhangAssistant Professor, University of Maryland, College ParkDirección de correo verificada de umd.edu
Dongsheng DingUniversity of PennsylvaniaDirección de correo verificada de seas.upenn.edu
Liyu ChenUniversity of Southern CaliforniaDirección de correo verificada de usc.edu
Hiteshi SharmaMicrosoftDirección de correo verificada de microsoft.com
Alberto BiettiFlatiron Institute, Simons FoundationDirección de correo verificada de nyu.edu
Miroslav DudikMicrosoft ResearchDirección de correo verificada de microsoft.com
Zhiwei Steven WuCarnegie Mellon UniversityDirección de correo verificada de andrew.cmu.edu
Mihailo R. JovanovicProfessor of Electrical and Computer Engineering, University of Southern CaliforniaDirección de correo verificada de usc.edu

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Chen-Yu Wei

Assistant Professor, University of Virginia

Dirección de correo verificada de virginia.edu - Página principal


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
More adaptive algorithms for adversarial bandits CY Wei, H Luo Conference On Learning Theory, 1263-1291, 2018	173	2018
Online reinforcement learning in stochastic games CY Wei, YT Hong, CJ Lu Advances in Neural Information Processing Systems 30, 2017	142	2017
A new algorithm for non-stationary contextual bandits: Efficient, optimal and parameter-free Y Chen, CW Lee, H Luo, CY Wei Conference on Learning Theory, 696-726, 2019	135	2019
Efficient contextual bandits in non-stationary worlds H Luo, CY Wei, A Agarwal, J Langford Conference On Learning Theory, 1739-1776, 2018	135	2018
Linear last-iterate convergence in constrained saddle-point optimization CY Wei, CW Lee, M Zhang, H Luo International Conference on Learning Representations, 2021	127*	2021
Last-iterate convergence of decentralized optimistic gradient descent/ascent in infinite-horizon competitive markov games CY Wei, CW Lee, M Zhang, H Luo Conference on learning theory, 4259-4299, 2021	104	2021
Non-stationary reinforcement learning without prior knowledge: An optimal black-box approach CY Wei, H Luo Conference on learning theory, 4300-4354, 2021	103	2021
Model-free reinforcement learning in infinite-horizon average-reward markov decision processes CY Wei, MJ Jahromi, H Luo, H Sharma, R Jain International conference on machine learning, 10170-10180, 2020	103	2020
Beating stochastic and adversarial semi-bandits optimally and simultaneously J Zimmert, H Luo, CY Wei International Conference on Machine Learning, 7683-7692, 2019	93	2019
Independent policy gradient for large-scale markov potential games: Sharper rates, function approximation, and game-agnostic convergence D Ding, CY Wei, K Zhang, M Jovanovic International Conference on Machine Learning, 5166-5220, 2022	74	2022
Tracking the best expert in non-stationary stochastic environments CY Wei, YT Hong, CJ Lu Advances in neural information processing systems 29, 2016	69	2016
Learning infinite-horizon average-reward mdps with linear function approximation CY Wei, MJ Jahromi, H Luo, R Jain International Conference on Artificial Intelligence and Statistics, 3007-3015, 2021	60	2021
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and mdps CW Lee, H Luo, CY Wei, M Zhang Advances in neural information processing systems 33, 15522-15533, 2020	60	2020
Efficient online portfolio with logarithmic regret H Luo, CY Wei, K Zheng Advances in neural information processing systems 31, 2018	57	2018
A model selection approach for corruption robust reinforcement learning CY Wei, C Dann, J Zimmert International Conference on Algorithmic Learning Theory, 1043-1096, 2022	52	2022
Improved path-length regret bounds for bandits S Bubeck, Y Li, H Luo, CY Wei Conference On Learning Theory, 508-528, 2019	50	2019
Policy optimization in adversarial mdps: Improved exploration via dilated bonuses H Luo, CY Wei, CW Lee Advances in Neural Information Processing Systems 34, 22931-22942, 2021	49	2021
Achieving near instance-optimality and minimax-optimality in stochastic and adversarial linear bandits simultaneously CW Lee, H Luo, CY Wei, M Zhang, X Zhang International Conference on Machine Learning, 6142-6151, 2021	48	2021
Impossible tuning made possible: A new expert algorithm and its applications L Chen, H Luo, CY Wei Conference on Learning Theory, 1216-1259, 2021	45	2021
Federated residual learning A Agarwal, J Langford, CY Wei arXiv preprint arXiv:2003.12880, 2020	40	2020

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