Baihe Huang - RankMe

38 papers A* 13A 1Journal 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	HuPER: A Human-Inspired Framework for Phonetic Perception. CoRR Chenxu Guo, Jiachen Lian, Yisi Liu, Baihe Huang, Shriyaa Narayanan, Cheol Jun Cho, Gopala Anumanchipalli
2026	J	`jnl`	PivotRL: High Accuracy Agentic Post-Training at Low Compute Cost. CoRR Junkeun Yi, Damon Mosk-Aoyama, Baihe Huang, Ritu Gala, Charles Wang, Sugam Dipak Devare, Khushi Bhardwaj, Abhibha Gupta, Oleksii Kuchaiev, Jiantao Jiao, Jian Zhang, Venkat Srinivasan
2026	J	`jnl`	Plan, Verify and Fill: A Structured Parallel Decoding Approach for Diffusion Language Models. CoRR Miao Li, Hanyang Jiang, Sikai Cheng, Hengyu Fu, Yuhang Cai, Baihe Huang, Tinghan Ye, Xuanzhou Chen, Pascal Van Hentenryck
2026	J	`jnl`	Towards Anytime-Valid Statistical Watermarking. CoRR Baihe Huang, Eric Xu, Kannan Ramchandran, Jiantao Jiao, Michael I. Jordan
2025	J	`jnl`	From Bits to Rounds: Parallel Decoding with Exploration for Diffusion Language Models. CoRR Hengyu Fu, Baihe Huang, Virginia Adams, Charles Wang, Venkat Srinivasan, Jiantao Jiao
2025	J	`jnl`	Sample Complexity and Representation Ability of Test-time Scaling Paradigms. CoRR Baihe Huang, Shanda Li, Tianhao Wu, Yiming Yang, Ameet Talwalkar, Kannan Ramchandran, Michael I. Jordan, Jiantao Jiao
2025	A*	`conf`	Sounding that Object: Interactive Object-Aware Image to Audio Generation. ICML Tingle Li, Baihe Huang, Xiaobin Zhuang, Dongya Jia, Jiawei Chen, Yuping Wang, Zhuo Chen, Gopala Anumanchipalli, Yuxuan Wang
2025	J	`jnl`	Sounding that Object: Interactive Object-Aware Image to Audio Generation. CoRR Tingle Li, Baihe Huang, Xiaobin Zhuang, Dongya Jia, Jiawei Chen, Yuping Wang, Zhuo Chen, Gopala Anumanchipalli, Yuxuan Wang
2024	A*	`conf`	Data Acquisition via Experimental Design for Data Markets. NeurIPS Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael I. Jordan, Ramesh Raskar
2024	J	`jnl`	Data Acquisition via Experimental Design for Decentralized Data Markets. CoRR Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael I. Jordan, Ramesh Raskar
2024	A*	`conf`	Enhancing Language Model Alignment: A Confidence-Based Approach to Label Smoothing. EMNLP Baihe Huang, Hiteshi Sharma, Yi Mao
2024	A*	`conf`	On Representation Complexity of Model-based and Model-free Reinforcement Learning. ICLR Hanlin Zhu, Baihe Huang, Stuart Russell
2024	A*	`conf`	Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity. NeurIPS Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
2024	J	`jnl`	Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity. CoRR Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
2024	A*	`conf`	Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. NeurIPS Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael I. Jordan, Jiantao Jiao, Yuandong Tian, Stuart J. Russell
2024	J	`jnl`	Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. CoRR Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael I. Jordan, Jiantao Jiao, Yuandong Tian, Stuart Russell
2023	J	`jnl`	Evaluating and Incentivizing Diverse Data Contributions in Collaborative Learning. CoRR Baihe Huang, Sai Praneeth Karimireddy, Michael I. Jordan
2023	J	`jnl`	On Representation Complexity of Model-based and Model-free Reinforcement Learning. CoRR Hanlin Zhu, Baihe Huang, Stuart Russell
2023	A	`conf`	Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition. AISTATS Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
2023	J	`jnl`	Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence. SIAM J. Optim. Wenhao Zhan, Shicong Cen, Baihe Huang, Yuxin Chen, Jason D. Lee, Yuejie Chi
2023	A*	`conf`	Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms. NeurIPS Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
2023	J	`jnl`	Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms. CoRR Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee
2023	J	`jnl`	Towards Optimal Statistical Watermarking. CoRR Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan
2022	J	`jnl`	A Dynamic Fast Gaussian Transform. CoRR Baihe Huang, Zhao Song, Omri Weinstein, Hengjie Zhang, Ruizhe Zhang
2022	A*	`conf`	Offline Reinforcement Learning with Realizability and Single-policy Concentrability. COLT Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason D. Lee
2022	J	`jnl`	Offline Reinforcement Learning with Realizability and Single-policy Concentrability. CoRR Wenhao Zhan, Baihe Huang, Audrey Huang, Nan Jiang, Jason D. Lee
2022	A*	`conf`	Solving SDP Faster: A Robust IPM Framework and Efficient Implementation. FOCS Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao, Ruizhe Zhang
2022	A*	`conf`	Towards General Function Approximation in Zero-Sum Markov Games. ICLR Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang
2021	A*	`conf`	FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis. ICML Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang
2021	J	`jnl`	FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis. CoRR Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang
2021	A*	`conf`	Going Beyond Linear RL: Sample Efficient Neural Function Approximation. NeurIPS Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
2021	J	`jnl`	Going Beyond Linear RL: Sample Efficient Neural Function Approximation. CoRR Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
2021	A*	`conf`	Optimal Gradient-based Algorithms for Non-concave Bandit Optimization. NeurIPS Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
2021	J	`jnl`	Optimal Gradient-based Algorithms for Non-concave Bandit Optimization. CoRR Baihe Huang, Kaixuan Huang, Sham M. Kakade, Jason D. Lee, Qi Lei, Runzhe Wang, Jiaqi Yang
2021	J	`jnl`	Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence. CoRR Wenhao Zhan, Shicong Cen, Baihe Huang, Yuxin Chen, Jason D. Lee, Yuejie Chi
2021	J	`jnl`	Solving Tall Dense SDPs in the Current Matrix Multiplication Time. CoRR Baihe Huang, Shunhua Jiang, Zhao Song, Runzhou Tao
2021	J	`jnl`	Towards General Function Approximation in Zero-Sum Markov Games. CoRR Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang
2020	J	`jnl`	InstaHide's Sample Complexity When Mixing Two Private Images. CoRR Baihe Huang, Zhao Song, Runzhou Tao, Ruizhe Zhang, Danyang Zhuo