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ORCIDYuting Wei 0001
Person information
- affiliation: University of Pennsylvania, Wharton School, Department of Statistics and Data Science, Philadelphia, PA, USA
- affiliation (2019 - 2021): Carnegie Mellon University, Department of Statistics and Data Science, Pittsburgh, PA, USA
- affiliation (2018 - 2019): Stanford University, Statistics Department. Stanford, CA, USA
- affiliation (PhD 2018): University of California at Berkeley, Department of Statistics, Berkeley, CA, USA
Other persons with the same name
- Yuting Wei (aka: Yu-Ting Wei) — disambiguation page
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2020 – today
- 2024
[j10]Gen Li, Yuting Wei
, Yuejie Chi, Yuxin Chen:
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model. Oper. Res. 72(1): 203-221 (2024)- [j9]Gen Li, Changxiao Cai, Yuxin Chen, Yuting Wei, Yuejie Chi:
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis. Oper. Res. 72(1): 222-236 (2024) - [j8]Shicong Cen, Yuting Wei, Yuejie Chi:
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization. J. Mach. Learn. Res. 25: 4:1-4:48 (2024) - [j7]Gen Li, Weichen Wu, Yuejie Chi, Cong Ma, Alessandro Rinaldo, Yuting Wei:
High-Probability Sample Complexities for Policy Evaluation With Linear Function Approximation. IEEE Trans. Inf. Theory 70(8): 5969-5999 (2024) - [c18]Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models. ICLR 2024 - [c17]Gen Li, Yu Huang, Timofey Efimov, Yuting Wei, Yuejie Chi, Yuxin Chen:
Accelerating Convergence of Score-Based Diffusion Models, Provably. ICML 2024 - [c16]Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei:
Theoretical insights for diffusion guidance: A case study for Gaussian mixture models. ICML 2024 - [i32]Gen Li, Yuting Wei:
A non-asymptotic distributional theory of approximate message passing for sparse and robust regression. CoRR abs/2401.03923 (2024) - [i31]Gen Li, Zhihan Huang, Yuting Wei:
Towards a mathematical theory for consistency training in diffusion models. CoRR abs/2402.07802 (2024) - [i30]Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei:
Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Models. CoRR abs/2403.01639 (2024) - [i29]Gen Li, Yu Huang, Timofey Efimov, Yuting Wei, Yuejie Chi, Yuxin Chen:
Accelerating Convergence of Score-Based Diffusion Models, Provably. CoRR abs/2403.03852 (2024) - [i28]Gen Li, Yuting Wei, Yuejie Chi, Yuxin Chen:
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models. CoRR abs/2408.02320 (2024) - [i27]Kevin Tan, Wei Fan, Yuting Wei:
Hybrid Reinforcement Learning Breaks Sample Size Barriers in Linear MDPs. CoRR abs/2408.04526 (2024) - 2023
- [j6]Gen Li, Yuting Wei, Yuejie Chi, Yuxin Chen:
Softmax policy gradient methods can take exponential time to converge. Math. Program. 201(1): 707-802 (2023) - [c15]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi:
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. NeurIPS 2023 - [i26]Gen Li, Wei Fan, Yuting Wei:
Approximate message passing from random initialization with applications to ℤ2 synchronization. CoRR abs/2302.03682 (2023) - [i25]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi:
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. CoRR abs/2305.16589 (2023) - [i24]Gen Li, Weichen Wu, Yuejie Chi, Cong Ma, Alessandro Rinaldo, Yuting Wei:
Sharp high-probability sample complexities for policy evaluation with linear function approximation. CoRR abs/2305.19001 (2023) - [i23]Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models. CoRR abs/2306.09251 (2023) - [i22]Tong Yang, Shicong Cen, Yuting Wei, Yuxin Chen, Yuejie Chi:
Federated Natural Policy Gradient Methods for Multi-task Reinforcement Learning. CoRR abs/2311.00201 (2023) - 2022
- [j5]Shicong Cen, Chen Cheng, Yuxin Chen, Yuting Wei, Yuejie Chi:
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization. Oper. Res. 70(4): 2563-2578 (2022) - [j4]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction. IEEE Trans. Inf. Theory 68(1): 448-473 (2022) - [c14]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity. ICML 2022: 19967-20025 - [c13]Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen:
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model. NeurIPS 2022 - [i21]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity. CoRR abs/2202.13890 (2022) - [i20]Gen Li, Laixi Shi, Yuxin Chen, Yuejie Chi, Yuting Wei:
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning. CoRR abs/2204.05275 (2022) - [i19]Pratik Patil, Arun Kumar Kuchibhotla, Yuting Wei, Alessandro Rinaldo:
Mitigating multiple descents: A model-agnostic framework for risk monotonization. CoRR abs/2205.12937 (2022) - [i18]Gen Li, Yuting Wei:
A Non-Asymptotic Framework for Approximate Message Passing in Spiked Models. CoRR abs/2208.03313 (2022) - [i17]Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen:
Minimax-Optimal Multi-Agent RL in Zero-Sum Markov Games With a Generative Model. CoRR abs/2208.10458 (2022) - 2021
- [j3]Chen Cheng, Yuting Wei, Yuxin Chen:
Tackling Small Eigen-Gaps: Fine-Grained Eigenvector Estimation and Inference Under Heteroscedastic Noise. IEEE Trans. Inf. Theory 67(11): 7380-7419 (2021) - [c12]Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar B. Shah:
Debiasing Evaluations That Are Biased by Evaluations. AAAI 2021: 10120-10128 - [c11]Pratik Patil, Yuting Wei, Alessandro Rinaldo, Ryan J. Tibshirani:
Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression. AISTATS 2021: 3178-3186 - [c10]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Softmax Policy Gradient Methods Can Take Exponential Time to Converge. COLT 2021: 3107-3110 - [c9]Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi:
Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning. ICML 2021: 6296-6306 - [c8]Gen Li, Yuxin Chen, Yuejie Chi, Yuantao Gu, Yuting Wei:
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting. NeurIPS 2021: 16671-16685 - [c7]Shicong Cen, Yuting Wei, Yuejie Chi:
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization. NeurIPS 2021: 27952-27964 - [i16]Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi:
Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning. CoRR abs/2102.06548 (2021) - [i15]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Softmax Policy Gradient Methods Can Take Exponential Time to Converge. CoRR abs/2102.11270 (2021) - [i14]Gen Li, Yuxin Chen, Yuejie Chi, Yuantao Gu, Yuting Wei:
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting. CoRR abs/2105.08024 (2021) - [i13]Shicong Cen, Yuting Wei, Yuejie Chi:
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization. CoRR abs/2105.15186 (2021) - [i12]Yue Li, Yuting Wei:
Minimum 𝓁1-norm interpolators: Precise asymptotics and multiple descent. CoRR abs/2110.09502 (2021) - 2020
- [j2]Yuting Wei, Martin J. Wainwright:
The Local Geometry of Testing in Ellipses: Tight Control via Localized Kolmogorov Widths. IEEE Trans. Inf. Theory 66(8): 5110-5129 (2020) - [c6]Chen Dan, Yuting Wei, Pradeep Ravikumar:
Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification. ICML 2020: 2345-2355 - [c5]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction. NeurIPS 2020 - [c4]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model. NeurIPS 2020 - [c3]Yue Li, Ilmun Kim, Yuting Wei:
Randomized tests for high-dimensional regression: A more efficient and powerful solution. NeurIPS 2020 - [i11]Chen Cheng, Yuting Wei, Yuxin Chen:
Inference for linear forms of eigenvectors under minimal eigenvalue separation: Asymmetry and heteroscedasticity. CoRR abs/2001.04620 (2020) - [i10]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model. CoRR abs/2005.12900 (2020) - [i9]Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen:
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction. CoRR abs/2006.03041 (2020) - [i8]Chen Dan, Yuting Wei, Pradeep Ravikumar:
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification. CoRR abs/2006.16384 (2020) - [i7]Shicong Cen, Chen Cheng, Yuxin Chen, Yuting Wei, Yuejie Chi:
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization. CoRR abs/2007.06558 (2020) - [i6]Michael Celentano, Andrea Montanari, Yuting Wei:
The Lasso with general Gaussian designs with applications to hypothesis testing. CoRR abs/2007.13716 (2020) - [i5]Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar B. Shah:
Debiasing Evaluations That are Biased by Evaluations. CoRR abs/2012.00714 (2020)
2010 – 2019
- 2019
- [j1]Yuting Wei, Fanny Yang, Martin J. Wainwright:
Early Stopping for Kernel Boosting Algorithms: A General Analysis With Localized Complexities. IEEE Trans. Inf. Theory 65(10): 6685-6703 (2019) - 2018
- [i4]Yuting Wei, Billy Fang, Martin J. Wainwright:
From Gauss to Kolmogorov: Localized Measures of Complexity for Ellipses. CoRR abs/1803.07763 (2018) - 2017
- [c2]Yuting Wei, Fanny Yang, Martin J. Wainwright:
Early stopping for kernel boosting algorithms: A general analysis with localized complexities. NIPS 2017: 6065-6075 - [i3]Yuting Wei, Martin J. Wainwright, Adityanand Guntuboyina:
The geometry of hypothesis testing over convex cones: Generalized likelihood tests and minimax radii. CoRR abs/1703.06810 (2017) - [i2]Yuting Wei, Fanny Yang, Martin J. Wainwright:
Early stopping for kernel boosting algorithms: A general analysis with localized complexities. CoRR abs/1707.01543 (2017) - [i1]Yuting Wei, Martin J. Wainwright:
The local geometry of testing in ellipses: Tight control via localized Kolomogorov widths. CoRR abs/1712.00711 (2017) - 2016
- [c1]Yuting Wei, Martin J. Wainwright:
Sharp minimax bounds for testing discrete monotone distributions. ISIT 2016: 2684-2688
Coauthor Index
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last updated on 2024-12-08 01:28 CET by the dblp team
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