Baihe Huang

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 26

Top Topics

Sample Complexity

Matrix Multiplication

Reinforcement Learning

Top Venues

Publications

Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael I. Jordan, Jiantao Jiao, Yuandong Tian, Stuart Russell
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. CoRR (2024)
Hanlin Zhu, Baihe Huang, Stuart Russell
On Representation Complexity of Model-based and Model-free Reinforcement Learning. ICLR (2024)
Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity. CoRR (2024)
Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael I. Jordan, Ramesh Raskar
Data Acquisition via Experimental Design for Decentralized Data Markets. CoRR (2024)
Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms. CoRR (2023)
Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition. AISTATS (2023)
Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms. NeurIPS (2023)
Baihe Huang, Sai Praneeth Karimireddy, Michael I. Jordan
Evaluating and Incentivizing Diverse Data Contributions in Collaborative Learning. CoRR (2023)
Hanlin Zhu, Baihe Huang, Stuart Russell
On Representation Complexity of Model-based and Model-free Reinforcement Learning. CoRR (2023)
Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan
Towards Optimal Statistical Watermarking. CoRR (2023)
Wenhao Zhan, Shicong Cen, Baihe Huang, Yuxin Chen, Jason D. Lee, Yuejie Chi
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence. SIAM J. Optim. 33 (2) (2023)
Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason D. Lee
Offline Reinforcement Learning with Realizability and Single-policy Concentrability. COLT (2022)
Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason D. Lee
Offline Reinforcement Learning with Realizability and Single-policy Concentrability. CoRR (2022)
Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang
Towards General Function Approximation in Zero-Sum Markov Games. ICLR (2022)
Baihe Huang, Zhao Song, Omri Weinstein, Hengjie Zhang, Ruizhe Zhang
A Dynamic Fast Gaussian Transform. CoRR (2022)
Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao, Ruizhe Zhang
Solving SDP Faster: A Robust IPM Framework and Efficient Implementation. FOCS (2022)
Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
Going Beyond Linear RL: Sample Efficient Neural Function Approximation. NeurIPS (2021)
Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization. CoRR (2021)
Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang
Towards General Function Approximation in Zero-Sum Markov Games. CoRR (2021)
Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization. NeurIPS (2021)
Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao
Solving Tall Dense SDPs in the Current Matrix Multiplication Time. CoRR (2021)
Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis. ICML (2021)
Wenhao Zhan, Shicong Cen, Baihe Huang, Yuxin Chen, Jason D. Lee, Yuejie Chi
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence. CoRR (2021)
Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
Going Beyond Linear RL: Sample Efficient Neural Function Approximation. CoRR (2021)
Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis. CoRR (2021)
Baihe Huang, Zhao Song, Runzhou Tao, Ruizhe Zhang, Danyang Zhuo
InstaHide's Sample Complexity When Mixing Two Private Images. CoRR (2020)