Baihe Huang

According to our database, Baihe Huang authored at least 17 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Data Acquisition via Experimental Design for Decentralized Data Markets.

Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael I. Jordan, Ramesh Raskar

CoRR, 2024

2023

Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence.

Wenhao Zhan, Shicong Cen, Baihe Huang, Yuxin Chen, Jason D. Lee, Yuejie Chi

SIAM J. Optim., June, 2023

Towards Optimal Statistical Watermarking.

Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan

CoRR, 2023

On Representation Complexity of Model-based and Model-free Reinforcement Learning.

Hanlin Zhu, Baihe Huang, Stuart Russell

CoRR, 2023

Evaluating and Incentivizing Diverse Data Contributions in Collaborative Learning.

Baihe Huang, Sai Praneeth Karimireddy, Michael I. Jordan

CoRR, 2023

Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms.

Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition.

Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

A Dynamic Fast Gaussian Transform.

Baihe Huang, Zhao Song, Omri Weinstein, Hengjie Zhang, Ruizhe Zhang

CoRR, 2022

Towards General Function Approximation in Zero-Sum Markov Games.

Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Solving SDP Faster: A Robust IPM Framework and Efficient Implementation.

Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao, Ruizhe Zhang

Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

Offline Reinforcement Learning with Realizability and Single-policy Concentrability.

Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason D. Lee

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis.

Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang

CoRR, 2021

Solving Tall Dense SDPs in the Current Matrix Multiplication Time.

Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao

CoRR, 2021

Optimal Gradient-based Algorithms for Non-concave Bandit Optimization.

Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Going Beyond Linear RL: Sample Efficient Neural Function Approximation.

Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis.

Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

InstaHide's Sample Complexity When Mixing Two Private Images.

Baihe Huang, Zhao Song, Runzhou Tao, Ruizhe Zhang, Danyang Zhuo

CoRR, 2020