Artiklar med krav på offentlig åtkomst - Yuting WeiLäs mer
Inte tillgänglig någonstans: 1
Sharp minimax bounds for testing discrete monotone distributions
Y Wei, MJ Wainwright
2016 IEEE International Symposium on Information Theory (ISIT), 2684-2688, 2016
Krav: US National Science Foundation
Tillgängliga någonstans: 30
Fast global convergence of natural policy gradient methods with entropy regularization
S Cen, C Cheng, Y Chen, Y Wei, Y Chi
Operations Research 70 (4), 2563-2578, 2022
Krav: US National Science Foundation, US Department of Defense
Breaking the sample size barrier in model-based reinforcement learning with a generative model
G Li, Y Wei, Y Chi, Y Chen
Operations Research 72 (1), 203-221, 2024
Krav: US National Science Foundation, US Department of Defense, National Natural …
Sample complexity of asynchronous Q-learning: Sharper analysis and variance reduction
G Li, Y Wei, Y Chi, Y Gu, Y Chen
IEEE Transactions on Information Theory 68 (1), 448-473, 2021
Krav: US National Science Foundation, US Department of Defense, National Natural …
The lasso with general gaussian designs with applications to hypothesis testing
M Celentano, A Montanari, Y Wei
The Annals of Statistics 51 (5), 2194-2220, 2023
Krav: US National Science Foundation, US Department of Defense
Pessimistic q-learning for offline reinforcement learning: Towards optimal sample complexity
L Shi, G Li, Y Wei, Y Chen, Y Chi
International conference on machine learning, 19967-20025, 2022
Krav: US National Science Foundation, US Department of Defense
Settling the sample complexity of model-based offline reinforcement learning
G Li, L Shi, Y Chen, Y Chi, Y Wei
The Annals of Statistics 52 (1), 233-260, 2024
Krav: US National Science Foundation, US Department of Defense
Is Q-learning minimax optimal? a tight sample complexity analysis
G Li, C Cai, Y Chen, Y Wei, Y Chi
Operations Research 72 (1), 222-236, 2024
Krav: US National Science Foundation, US Department of Defense
Early stopping for kernel boosting algorithms: A general analysis with localized complexities
Y Wei, F Yang, MJ Wainwright
IEEE Transactions on Information Theory 65 (10), 6685-6703, 2019
Krav: US National Science Foundation, US Department of Defense
Fast policy extragradient methods for competitive games with entropy regularization
S Cen, Y Wei, Y Chi
Advances in Neural Information Processing Systems 34, 27952-27964, 2021
Krav: US National Science Foundation, US Department of Defense
Towards faster non-asymptotic convergence for diffusion-based generative models
G Li, Y Wei, Y Chen, Y Chi
arXiv preprint arXiv:2306.09251, 2023
Krav: US National Science Foundation, US Department of Defense
Softmax Policy Gradient Methods Can Take Exponential Time to Converge
G Li, Y Wei, Y Chi, Y Chen
Mathematical Programming, 2021
Krav: US National Science Foundation, US Department of Defense, National Natural …
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification
C Dan, Y Wei, P Ravikumar
International Conference on Machine Learning, 2345-2355, 2020
Krav: US National Science Foundation, US Department of Defense
Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression
P Patil, Y Wei, A Rinaldo, R Tibshirani
International Conference on Artificial Intelligence and Statistics, 3178-3186, 2021
Krav: US National Science Foundation, US Department of Defense
Derandomizing knockoffs
Z Ren, Y Wei, E Candès
Journal of the American Statistical Association 118 (542), 948-958, 2023
Krav: US National Science Foundation, US Department of Defense
The curious price of distributional robustness in reinforcement learning with a generative model
L Shi, G Li, Y Wei, Y Chen, M Geist, Y Chi
Advances in Neural Information Processing Systems 36, 79903-79917, 2023
Krav: US National Science Foundation, US Department of Defense
Tackling small eigen-gaps: Fine-grained eigenvector estimation and inference under heteroscedastic noise
C Cheng, Y Wei, Y Chen
IEEE Transactions on Information Theory 67 (11), 7380-7419, 2021
Krav: US National Science Foundation, US Department of Defense
Minimax-optimal multi-agent RL in zero-sum Markov games with a generative model
G Li, Y Chi, Y Wei, Y Chen
Advances in Neural Information Processing Systems, 2022
Krav: US National Science Foundation, US Department of Defense
Integration and transfer learning of single-cell transcriptomes via cFIT
M Peng, Y Li, B Wamsley, Y Wei, K Roeder
Proceedings of the National Academy of Sciences 118 (10), 2021
Krav: US National Science Foundation, US National Institutes of Health
Sample-efficient reinforcement learning is feasible for linearly realizable MDPs with limited revisiting
G Li, Y Chen, Y Chi, Y Gu, Y Wei
Advances in Neural Information Processing Systems 34, 16671-16685, 2021
Krav: US National Science Foundation, US Department of Defense, National Natural …
Publikations- och finansieringsuppgifter tas fram automatiskt av ett datorprogram.