Heyang Zhao - RankMe

28 papers A* 10Journal 14Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Near-Optimal Regret for KL-Regularized Multi-Armed Bandits. CoRR Kaixuan Ji, Qingyue Zhao, Heyang Zhao, Qiwei Di, Quanquan Gu
2025	—	`conf`	A 0.16mm CICC Heyang Zhao, Yuxuan He, Yunsong Tao, Zhishuai Zhang, Yong Chen, Yi Zhong, Lu Jie, Nan Sun
2025	J	`jnl`	Best-of-Majority: Minimax-Optimal Strategy for Pass@ CoRR Qiwei Di, Kaixuan Ji, Xuheng Li, Heyang Zhao, Quanquan Gu
2025	A*	`conf`	Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration. ICLR Heyang Zhao, Xingrui Yu, David Mark Bossens, Ivor W. Tsang, Quanquan Gu
2025	J	`jnl`	Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration. CoRR Heyang Zhao, Xingrui Yu, David Mark Bossens, Ivor W. Tsang, Quanquan Gu
2025	—	`conf`	CGCA-KAN: Correction-Guided Cluster-Aware Attention and KAN Enhanced Architecture for Medical Image Segmentation. BIBM Peng Zhang, Yida Wu, Chen Liu, Heyang Zhao, Xingyu Liu, Zeyu Liu, Guanglei Zhang, Wenjian Wang
2025	A*	`conf`	Logarithmic Regret for Online KL-Regularized Reinforcement Learning. ICML Heyang Zhao, Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2025	J	`jnl`	Logarithmic Regret for Online KL-Regularized Reinforcement Learning. CoRR Heyang Zhao, Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2025	J	`jnl`	Nearly Optimal Sample Complexity of Offline KL-Regularized Contextual Bandits under Single-Policy Concentrability. CoRR Qingyue Zhao, Kaixuan Ji, Heyang Zhao, Tong Zhang, Quanquan Gu
2024	A*	`conf`	A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation. NeurIPS Heyang Zhao, Jiafan He, Quanquan Gu
2024	A*	`conf`	Feel-Good Thompson Sampling for Contextual Dueling Bandits. ICML Xuheng Li, Heyang Zhao, Quanquan Gu
2024	J	`jnl`	Feel-Good Thompson Sampling for Contextual Dueling Bandits. CoRR Xuheng Li, Heyang Zhao, Quanquan Gu
2024	A*	`conf`	Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning. ICLR Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu
2024	—	`conf`	S-lemma On Three Non-homogeneous Quadratic Functions And Its Applications In Signal Recovery. ICCIP Heyang Zhao, Mengxiao Zhang, Wenbao Ai
2024	J	`jnl`	Sharp Analysis for KL-Regularized Contextual Bandits and RLHF. CoRR Heyang Zhao, Chenlu Ye, Quanquan Gu, Tong Zhang
2024	A*	`conf`	Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits. ICLR Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu
2023	J	`jnl`	A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation. CoRR Heyang Zhao, Jiafan He, Quanquan Gu
2023	A*	`conf`	Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes. ICML Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu
2023	A*	`conf`	Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits. ICML Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu
2023	J	`jnl`	Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning. CoRR Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu
2023	J	`jnl`	Variance-Aware Regret Bounds for Stochastic Contextual Dueling Bandits. CoRR Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu
2023	A*	`conf`	Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. COLT Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
2023	J	`jnl`	Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. CoRR Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
2022	J	`jnl`	Bandit Learning with General Function Classes: Heteroscedastic Noise and Variance-dependent Regret Bounds. CoRR Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu
2022	J	`jnl`	Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes. CoRR Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu
2022	A*	`conf`	ProvTalk: Towards Interpretable Multi-level Provenance Analysis in Networking Functions Virtualization (NFV). NDSS Azadeh Tabiban, Heyang Zhao, Yosr Jarraya, Makan Pourzandi, Mengyuan Zhang, Lingyu Wang
2022	—	`conf`	VinciDecoder: Automatically Interpreting Provenance Graphs into Textual Forensic Reports with Application to OpenStack. NordSec Azadeh Tabiban, Heyang Zhao, Yosr Jarraya, Makan Pourzandi, Lingyu Wang
2021	J	`jnl`	Linear Contextual Bandits with Adversarial Corruptions. CoRR Heyang Zhao, Dongruo Zhou, Quanquan Gu