Heyang Zhao

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 15

Top Topics

Linear Regression

Markov Decision Process

Reinforcement Learning

Top Venues

Publications

Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu
Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits. ICLR (2024)
Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning. ICLR (2024)
Xuheng Li, Heyang Zhao, Quanquan Gu
Feel-Good Thompson Sampling for Contextual Dueling Bandits. CoRR (2024)
Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes. ICML (2023)
Heyang Zhao, Jiafan He, Quanquan Gu
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation. CoRR (2023)
Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. CoRR (2023)
Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning. CoRR (2023)
Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. COLT (2023)
Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu
Variance-Aware Regret Bounds for Stochastic Contextual Dueling Bandits. CoRR (2023)
Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits. ICML (2023)
Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu
Bandit Learning with General Function Classes: Heteroscedastic Noise and Variance-dependent Regret Bounds. CoRR (2022)
Azadeh Tabiban, Heyang Zhao, Yosr Jarraya, Makan Pourzandi, Lingyu Wang
VinciDecoder: Automatically Interpreting Provenance Graphs into Textual Forensic Reports with Application to OpenStack. NordSec (2022)
Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes. CoRR (2022)
Azadeh Tabiban, Heyang Zhao, Yosr Jarraya, Makan Pourzandi, Mengyuan Zhang, Lingyu Wang
ProvTalk: Towards Interpretable Multi-level Provenance Analysis in Networking Functions Virtualization (NFV). NDSS (2022)
Heyang Zhao, Dongruo Zhou, Quanquan Gu
Linear Contextual Bandits with Adversarial Corruptions. CoRR (2021)