2025

• Efficient Reinforcement Learning in Probabilistic Reward Machines.

  Xiaofeng Lin*, Xuezhou Zhang

  AAAI 2025 (Oral)

2024

• State-free Reinforcement Learning.

  Mingyu Chen*, Aldo Pacchiano, Xuezhou Zhang

  Neurips 2024

• Improved Algorithms for Adversarial Bandits with Unbounded Losses.

  Mingyu Chen*, Xuezhou Zhang

  ArXiv Preprint

• Scale-free Adversarial Reinforcement Learning.

  Mingyu Chen*, Xuezhou Zhang

  COLT 2024

• Exact policy recovery in offline RL with both heavy-tailed rewards and data corruption.

  Yiding Chen*, Xuezhou Zhang, Qiaomin Xie, and Xiaojin Zhu

  AAAI 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

  Neurips 2023

• Provably Efficient Representation Learning with Tractable Planning in LowRank POMDP.

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

  ICML 2023

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

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

  ICLR 2023

• Byzantine-Robust Online and Offline Distributed Reinforcement Learning

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

  AISTATS 2023

• Provable Benefits of Representational Transfer in Reinforcement Learning

  (α-β) Alekh Agarwal*, Yuda Song*, Wen Sun*, Kaiwen Wang*, Mengdi Wang*, Xuezhou Zhang*

  COLT 2023

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

  Neurips 2022

• Provable defense against backdoor policies in reinforcement learning.

  Shubham Bharti*, Xuezhou Zhang, Adish Singla, and Xiaojin Zhu.

  Neurips 2022

• Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks

  Shuoguang Yang*, Xuezhou Zhang, Mengdi Wang

  Neurips 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

  ICML 2022

• Optimal Estimation of Policy Gradient via Double Fitted Iteration

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

  ICML 2022

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

  Ruiqi Zhang*, Xuezhou Zhang, Chengzhuo Ni, Mengdi Wang

  ICML 2022

• Corruption-robust offline reinforcement learning

  Xuezhou Zhang*, Yiding Chen, Xiaojin Zhu, Wen Sun

  AISTATS 2022

2021

• Neural additive models: Interpretable machine learning with neural nets

  Rishabh Agarwal*, Levi Melnick*, Nicholas Frosst, Xuezhou Zhang, Ben Lengerich, Rich Caruana, Geoffrey E Hinton

  Neurips 2021 (Oral)

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

  Masatoshi Uehara*, Xuezhou Zhang, Wen Sun

  ICLR 2021 (Spotlight)

• Robust policy gradient against strong data corruption

  Xuezhou Zhang*, Yiding Chen, Xiaojin Zhu, Wen Sun

  ICML 2021

• The sample complexity of teaching by reinforcement on q-learning

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

  AAAI 2021

• Controllable and diverse text generation in e-commerce

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

  WWW 2021

2020

• Task-agnostic exploration in reinforcement learning

  Xuezhou Zhang*, Yuzhe Ma, Adish Singla

  Neurips 2020

• Adaptive reward-poisoning attacks against reinforcement learning

  Xuezhou Zhang*, Yuzhe Ma, Adish Singla, Xiaojin Zhu

  ICML 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

  CogSci 2020

• Online Data Poisoning Attack

  Xuezhou Zhang*, Laurent Lessard, Xiaojin Zhu

  L4DC 2020 (Oral)

2019

• Policy poisoning in batch reinforcement learning and control

  Yuzhe Ma*, Xuezhou Zhang, Wen Sun, Xiaojin Zhu

  Neurips 2019

• Axiomatic Interpretability for Multiclass Additive Models

  Xuezhou Zhang*, Sarah Tan, Paul Koch, Urszula Chajewska, Rich Caruana

  KDD 2019 (Oral)

• An Optimal Control Approach to Sequential Machine Teaching

  (α-β) Laurent Lessard, Xuezhou Zhang, Xiaojin Zhu

  AISTATS 2019

2018

• Teacher Improves Learning by Selecting a Training Subset

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

  AISTATS 2018

• Training set debugging using trusted items

  Xuezhou Zhang*, Xiaojin Zhu, Stephen J Wright

  AAAI 2018 (Oral)

• Training set camouflage

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

  GameSec 2018 (Oral)