Xuezhou Zhang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 61

Top Topics

Policy Gradient

Reinforcement Learning

Markov Decision Processes

Top Venues

Publications

Mingyu Chen, Xuezhou Zhang
Scale-free Adversarial Reinforcement Learning. CoRR (2024)
Yiding Chen, Xuezhou Zhang, Qiaomin Xie, Xiaojin Zhu
Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption. AAAI (2024)
Mingyu Chen, Xuezhou Zhang
Scale-free Adversarial Reinforcement Learning. COLT (2024)
Shuoguang Yang, Xuezhou Zhang, Mengdi Wang
Federated Multi-Level Optimization over Decentralized Networks. CoRR (2023)
Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. CoRR (2023)
Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. AISTATS (2023)
Mingyu Chen, Xuezhou Zhang
Improved Algorithms for Adversarial Bandits with Unbounded Losses. CoRR (2023)
Chengzhuo Ni, Yuda Song, Xuezhou Zhang, Zihan Ding, Chi Jin, Mengdi Wang
Representation Learning for Low-rank General-sum Markov Games. ICLR (2023)
Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback. NeurIPS (2023)
Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP. ICML (2023)
Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP. CoRR (2023)
Alekh Agarwal, Yuda Song, Wen Sun, Kaiwen Wang, Mengdi Wang, Xuezhou Zhang
Provable Benefits of Representational Transfer in Reinforcement Learning. COLT (2023)
Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Xiaojin Zhu
Provable Defense against Backdoor Policies in Reinforcement Learning. CoRR (2022)
Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong, Csaba Szepesvári, Mengdi Wang
Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization. CoRR (2022)
Chengzhuo Ni, Ruiqi Zhang, Xiang Ji, Xuezhou Zhang, Mengdi Wang
Optimal Estimation of Off-Policy Policy Gradient via Double Fitted Iteration. CoRR (2022)
Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Jerry Zhu
Provable Defense against Backdoor Policies in Reinforcement Learning. NeurIPS (2022)
Kaixuan Huang, Yu Wu, Xuezhou Zhang, Shenyinying Tu, Qingyun Wu, Mengdi Wang, Huazheng Wang
Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization. CoRR (2022)
Masatoshi Uehara, Xuezhou Zhang, Wen Sun
Representation Learning for Online and Offline RL in Low-rank MDPs. ICLR (2022)
Ruiqi Zhang, Xuezhou Zhang, Chengzhuo Ni, Mengdi Wang
Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory. CoRR (2022)
Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. CoRR (2022)
Shuoguang Yang, Xuezhou Zhang, Mengdi Wang
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks. CoRR (2022)
Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong, Csaba Szepesvári, Mengdi Wang
Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization. NeurIPS (2022)
Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal, Wen Sun
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach. CoRR (2022)
Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal, Wen Sun
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach. ICML (2022)
Ruiqi Zhang, Xuezhou Zhang, Chengzhuo Ni, Mengdi Wang
Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory. ICML (2022)
Chengzhuo Ni, Yuda Song, Xuezhou Zhang, Chi Jin, Mengdi Wang
Representation Learning for General-sum Low-rank Markov Games. CoRR (2022)
Chengzhuo Ni, Ruiqi Zhang, Xiang Ji, Xuezhou Zhang, Mengdi Wang
Optimal Estimation of Policy Gradient via Double Fitted Iteration. ICML (2022)
Shuoguang Yang, Xuezhou Zhang, Mengdi Wang
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks. NeurIPS (2022)
Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun
Corruption-robust Offline Reinforcement Learning. AISTATS (2022)
Alekh Agarwal, Yuda Song, Wen Sun, Kaiwen Wang, Mengdi Wang, Xuezhou Zhang
Provable Benefits of Representational Transfer in Reinforcement Learning. CoRR (2022)
Amin Rakhsha, Xuezhou Zhang, Xiaojin Zhu, Adish Singla
Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments. CoRR (2021)
Huajie Shao, Jun Wang, Haohong Lin, Xuezhou Zhang, Aston Zhang, Heng Ji, Tarek F. Abdelzaher
Controllable and Diverse Text Generation in E-commerce. CoRR (2021)
Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Jerry Zhu
Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners. CogSci (2021)
Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Benjamin J. Lengerich, Rich Caruana, Geoffrey E. Hinton
Neural Additive Models: Interpretable Machine Learning with Neural Nets. NeurIPS (2021)
Huajie Shao, Jun Wang, Haohong Lin, Xuezhou Zhang, Aston Zhang, Heng Ji, Tarek F. Abdelzaher
Controllable and Diverse Text Generation in E-commerce. WWW (2021)
Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu
The Sample Complexity of Teaching by Reinforcement on Q-Learning. AAAI (2021)
Masatoshi Uehara, Xuezhou Zhang, Wen Sun
Representation Learning for Online and Offline RL in Low-rank MDPs. CoRR (2021)
Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun
Corruption-Robust Offline Reinforcement Learning. CoRR (2021)
Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun
Robust Policy Gradient against Strong Data Corruption. ICML (2021)
Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun
Robust Policy Gradient against Strong Data Corruption. CoRR (2021)
Rishabh Agarwal, Nicholas Frosst, Xuezhou Zhang, Rich Caruana, Geoffrey E. Hinton
Neural Additive Models: Interpretable Machine Learning with Neural Nets. CoRR (2020)
Xuezhou Zhang, Yuzhe Ma, Adish Singla
Task-agnostic Exploration in Reinforcement Learning. CoRR (2020)
Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu
Adaptive Reward-Poisoning Attacks against Reinforcement Learning. ICML (2020)
Xuezhou Zhang, Yuzhe Ma, Adish Singla
Task-agnostic Exploration in Reinforcement Learning. NeurIPS (2020)
Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu
Adaptive Reward-Poisoning Attacks against Reinforcement Learning. CoRR (2020)
Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu
The Teaching Dimension of Q-learning. CoRR (2020)
Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Xiaojin Zhu
Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners. CoRR (2020)
Xuezhou Zhang, Xiaojin Zhu, Laurent Lessard
Online Data Poisoning Attacks. L4DC (2020)
Xuezhou Zhang, Xiaojin Zhu
Online Data Poisoning Attack. CoRR (2019)
Yuzhe Ma, Xuezhou Zhang, Wen Sun, Xiaojin Zhu
Policy Poisoning in Batch Reinforcement Learning and Control. CoRR (2019)
Yuzhe Ma, Xuezhou Zhang, Wen Sun, Jerry Zhu
Policy Poisoning in Batch Reinforcement Learning and Control. NeurIPS (2019)
Laurent Lessard, Xuezhou Zhang, Xiaojin Zhu
An Optimal Control Approach to Sequential Machine Teaching. AISTATS (2019)
Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana
Axiomatic Interpretability for Multiclass Additive Models. KDD (2019)
Xuezhou Zhang, Xiaojin Zhu, Stephen J. Wright
Training Set Debugging Using Trusted Items. CoRR (2018)
Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana
Interpretability is Harder in the Multiclass Setting: Axiomatic Interpretability for Multiclass Additive Models. CoRR (2018)
Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu
Teacher Improves Learning by Selecting a Training Subset. CoRR (2018)
Ayon Sen, Scott Alfeld, Xuezhou Zhang, Ara Vartanian, Yuzhe Ma, Xiaojin Zhu
Training Set Camouflage. GameSec (2018)
Laurent Lessard, Xuezhou Zhang, Xiaojin Zhu
An Optimal Control Approach to Sequential Machine Teaching. CoRR (2018)
Ayon Sen, Scott Alfeld, Xuezhou Zhang, Ara Vartanian, Yuzhe Ma, Xiaojin Zhu
Training Set Camouflage. CoRR (2018)
Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu
Teacher Improves Learning by Selecting a Training Subset. AISTATS (2018)
Xuezhou Zhang, Xiaojin Zhu, Stephen J. Wright
Training Set Debugging Using Trusted Items. AAAI (2018)