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Chen-Yu Wei
Chen-Yu Wei
Assistant Professor, University of Virginia
Подтвержден адрес электронной почты в домене virginia.edu - Главная страница
Название
Процитировано
Процитировано
Год
More adaptive algorithms for adversarial bandits
CY Wei, H Luo
Conference On Learning Theory, 1263-1291, 2018
1892018
Online reinforcement learning in stochastic games
CY Wei, YT Hong, CJ Lu
Advances in Neural Information Processing Systems 30, 2017
1502017
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
1452019
Linear last-iterate convergence in constrained saddle-point optimization
CY Wei, CW Lee, M Zhang, H Luo
International Conference on Learning Representations, 2021
143*2021
Efficient contextual bandits in non-stationary worlds
H Luo, CY Wei, A Agarwal, J Langford
Conference On Learning Theory, 1739-1776, 2018
1402018
Non-stationary reinforcement learning without prior knowledge: An optimal black-box approach
CY Wei, H Luo
Conference on learning theory, 4300-4354, 2021
1222021
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
1142020
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
1132021
Beating stochastic and adversarial semi-bandits optimally and simultaneously
J Zimmert, H Luo, CY Wei
International Conference on Machine Learning, 7683-7692, 2019
962019
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
852022
Tracking the best expert in non-stationary stochastic environments
CY Wei, YT Hong, CJ Lu
Advances in neural information processing systems 29, 2016
712016
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
662020
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
652021
A model selection approach for corruption robust reinforcement learning
CY Wei, C Dann, J Zimmert
International Conference on Algorithmic Learning Theory, 1043-1096, 2022
612022
Efficient online portfolio with logarithmic regret
H Luo, CY Wei, K Zheng
Advances in neural information processing systems 31, 2018
612018
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
552021
Personalization improves privacy-accuracy tradeoffs in federated learning
A Bietti, CY Wei, M Dudik, J Langford, S Wu
International Conference on Machine Learning, 1945-1962, 2022
542022
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
532021
Improved path-length regret bounds for bandits
S Bubeck, Y Li, H Luo, CY Wei
Conference On Learning Theory, 508-528, 2019
532019
Impossible tuning made possible: A new expert algorithm and its applications
L Chen, H Luo, CY Wei
Conference on Learning Theory, 1216-1259, 2021
482021
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