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 | 196 | 2022 |

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 | 140* | 2024 |

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 | 110 | 2021 |

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 | 91 | 2023 |

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 | 88 | 2022 |

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 | 85 | 2019 |

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 | 75 | 2024 |

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 | 72 | 2024 |

Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization S Cen, Y Wei, Y Chi Journal of Machine Learning Research 25 (4), 1-48, 2024 | 62 | 2024 |

Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification C Dan, Y Wei, P Ravikumar International Conference on Machine Learning, 2345-2355, 2020 | 54 | 2020 |

Softmax Policy Gradient Methods Can Take Exponential Time to Converge G Li, Y Wei, Y Chi, Y Chen accepted to Mathematical Programming, 2021 | 50 | 2021 |

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 | 44 | 2021 |

Derandomizing knockoffs Z Ren, Y Wei, E Candès Journal of the American Statistical Association 118 (542), 948-958, 2023 | 33 | 2023 |

Towards faster non-asymptotic convergence for diffusion-based generative models G Li, Y Wei, Y Chen, Y Chi arXiv preprint arXiv:2306.09251, 2023 | 32 | 2023 |

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 | 32 | 2021 |

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 | 31 | 2021 |

The geometry of hypothesis testing over convex cones: Generalized likelihood ratio tests and minimax radii Y Wei, MJ Wainwright, A Guntuboyina Annals of Statistics 47 (2), 994-1024, 2019 | 30* | 2019 |

Minimum -norm interpolators: Precise asymptotics and multiple descent Y Li, Y Wei arXiv preprint arXiv:2110.09502, 2021 | 29 | 2021 |

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 | 28* | 2021 |

A non-asymptotic framework for approximate message passing in spiked models G Li, Y Wei arXiv preprint arXiv:2208.03313, 2022 | 26 | 2022 |