Xuezhou Zhang

According to our database, Xuezhou Zhang authored at least 43 papers between 2018 and 2024.

Collaborative distances:

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

2024

Scale-free Adversarial Reinforcement Learning.

Mingyu Chen, Xuezhou Zhang

CoRR, 2024

Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption.

Yiding Chen, Xuezhou Zhang, Qiaomin Xie, Xiaojin Zhu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback.

Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li

CoRR, 2023

Federated Multi-Level Optimization over Decentralized Networks.

Shuoguang Yang, Xuezhou Zhang, Mengdi Wang

CoRR, 2023

Improved Algorithms for Adversarial Bandits with Unbounded Losses.

Mingyu Chen, Xuezhou Zhang

CoRR, 2023

Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback.

Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Xuezhou Zhang, Shuai Li

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

Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP.

Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang

Proceedings of the International Conference on Machine Learning, 2023

Representation Learning for Low-rank General-sum Markov Games.

Chengzhuo Ni, Yuda Song, Xuezhou Zhang, Zihan Ding, Chi Jin, Mengdi Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Provable Benefits of Representational Transfer in Reinforcement Learning.

Alekh Agarwal, Yuda Song, Wen Sun, Kaiwen Wang, Mengdi Wang, Xuezhou Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Byzantine-Robust Online and Offline Distributed Reinforcement Learning.

Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu

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

2022

Provable Defense against Backdoor Policies in Reinforcement Learning.

Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Xiaojin Zhu

CoRR, 2022

Representation Learning for General-sum Low-rank Markov Games.

Chengzhuo Ni, Yuda Song, Xuezhou Zhang, Chi Jin, Mengdi Wang

CoRR, 2022

Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization.

Kaixuan Huang, Yu Wu, Xuezhou Zhang, Shenyinying Tu, Qingyun Wu, Mengdi Wang, Huazheng Wang

CoRR, 2022

Optimal Estimation of Off-Policy Policy Gradient via Double Fitted Iteration.

Chengzhuo Ni, Ruiqi Zhang, Xiang Ji, Xuezhou Zhang, Mengdi Wang

CoRR, 2022

Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization.

Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong, Csaba Szepesvári, Mengdi Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks.

Shuoguang Yang, Xuezhou Zhang, Mengdi Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Provable Defense against Backdoor Policies in Reinforcement Learning.

Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Jerry Zhu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory.

Ruiqi Zhang, Xuezhou Zhang, Chengzhuo Ni, Mengdi Wang

Proceedings of the International Conference on Machine Learning, 2022

Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach.

Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal, Wen Sun

Proceedings of the International Conference on Machine Learning, 2022

Optimal Estimation of Policy Gradient via Double Fitted Iteration.

Chengzhuo Ni, Ruiqi Zhang, Xiang Ji, Xuezhou Zhang, Mengdi Wang

Proceedings of the International Conference on Machine Learning, 2022

Representation Learning for Online and Offline RL in Low-rank MDPs.

Masatoshi Uehara, Xuezhou Zhang, Wen Sun

Proceedings of the Tenth International Conference on Learning Representations, 2022

Corruption-robust Offline Reinforcement Learning.

Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Corruption-Robust Offline Reinforcement Learning.

Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun

CoRR, 2021

Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments.

Amin Rakhsha, Xuezhou Zhang, Xiaojin Zhu, Adish Singla

CoRR, 2021

Controllable and Diverse Text Generation in E-commerce.

Huajie Shao, Jun Wang, Haohong Lin, Xuezhou Zhang, Aston Zhang, Heng Ji, Tarek F. Abdelzaher

Proceedings of the WWW '21: The Web Conference 2021, 2021

Neural Additive Models: Interpretable Machine Learning with Neural Nets.

Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Benjamin J. Lengerich, Rich Caruana, Geoffrey E. Hinton

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

Robust Policy Gradient against Strong Data Corruption.

Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun

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

The Sample Complexity of Teaching by Reinforcement on Q-Learning.

Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners.

Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Xiaojin Zhu

CoRR, 2020

The Teaching Dimension of Q-learning.

Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu

CoRR, 2020

Neural Additive Models: Interpretable Machine Learning with Neural Nets.

Rishabh Agarwal, Nicholas Frosst, Xuezhou Zhang, Rich Caruana, Geoffrey E. Hinton

CoRR, 2020

Task-agnostic Exploration in Reinforcement Learning.

Xuezhou Zhang, Yuzhe Ma, Adish Singla

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Data Poisoning Attacks.

Xuezhou Zhang, Xiaojin Zhu, Laurent Lessard

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Adaptive Reward-Poisoning Attacks against Reinforcement Learning.

Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Policy Poisoning in Batch Reinforcement Learning and Control.

Yuzhe Ma, Xuezhou Zhang, Wen Sun, Xiaojin Zhu

CoRR, 2019

Online Data Poisoning Attack.

Xuezhou Zhang, Xiaojin Zhu

CoRR, 2019

Policy Poisoning in Batch Reinforcement Learning and Control.

Yuzhe Ma, Xuezhou Zhang, Wen Sun, Jerry Zhu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Axiomatic Interpretability for Multiclass Additive Models.

Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

An Optimal Control Approach to Sequential Machine Teaching.

Laurent Lessard, Xuezhou Zhang, Xiaojin Zhu

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Interpretability is Harder in the Multiclass Setting: Axiomatic Interpretability for Multiclass Additive Models.

Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana

CoRR, 2018

Training Set Camouflage.

Ayon Sen, Scott Alfeld, Xuezhou Zhang, Ara Vartanian, Yuzhe Ma, Xiaojin Zhu

Proceedings of the Decision and Game Theory for Security - 9th International Conference, 2018

Teacher Improves Learning by Selecting a Training Subset.

Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Training Set Debugging Using Trusted Items.

Xuezhou Zhang, Xiaojin Zhu, Stephen J. Wright

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018