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Xuezhou Zhang

26 papers · 2018–2025 · 7 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+10 more ↓ πŸ—ΊοΈ Taxonomy Completionist (44) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
🀝 Dynamic Duo (11) 🧭 Keyword Pioneer πŸ† Grand Slam πŸ‘‘ Triple Crown ⚑ Prolific Year Β· Productive πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze πŸš€ Conference Pioneer 🌈 Renaissance Researcher (5) πŸ—ƒοΈ Keyword Collector (131)

Venues

NeurIPS (8) ICML (6) AISTATS (4) AAAI (3) COLT (2) ICLR (2) L4DC (1)

Top co-authors

Xiaojin Zhu (11) Mengdi Wang (9) Wen Sun (6) Yuzhe Ma (5) Chengzhuo Ni (4) Adish Singla (4) Yiding Chen (4) Yuda Song (3) Alekh Agarwal (2) Masatoshi Uehara (2)

Research topics

Machine Learning (24) Reinforcement Learning (16) Learning Types (15) Artificial Intelligence (14) Methods (14) Optimization & Theory (14) Core AI (11) Core Methods (7) Learning Paradigms (5) Mathematics & Optimization (2) Applications (2) Optimization (2) Deep Learning (1) Interdisciplinary (1) Security & Privacy (1)

Keywords

reinforcement learning (9) representation learning (6) regret bound (6) sample complexity (5) adversarial learning (3) offline reinforcement learning (3) sample efficiency (2) robust mean estimation (2) maximum likelihood estimation (2) online learning (2) asymptotic normality (2) policy optimization (2) pessimistic value iteration (2) policy gradient (2) adversarial attack (2) value iteration (2) low-rank mdp (2) convex optimization (1) data poisoning (1) adversarial robustness (1)

Papers

Efficient Reinforcement Learning in Probabilistic Reward Machines AAAI 2025 Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption AAAI 2024 Scale-free Adversarial Reinforcement Learning COLT 2024 State-free Reinforcement Learning NeurIPS 2024 Byzantine-Robust Online and Offline Distributed Reinforcement Learning AISTATS 2023 Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback NeurIPS 2023 Provable Benefits of Representational Transfer in Reinforcement Learning COLT 2023 Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP ICML 2023 Representation Learning for Low-rank General-sum Markov Games ICLR 2023 Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization NeurIPS 2022 Corruption-robust Offline Reinforcement Learning AISTATS 2022 Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks NeurIPS 2022 Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach ICML 2022 Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory ICML 2022 Optimal Estimation of Policy Gradient via Double Fitted Iteration ICML 2022 Provable Defense against Backdoor Policies in Reinforcement Learning NeurIPS 2022 Representation Learning for Online and Offline RL in Low-rank MDPs ICLR 2022 Neural Additive Models: Interpretable Machine Learning with Neural Nets NeurIPS 2021 Robust Policy Gradient against Strong Data Corruption ICML 2021 The Sample Complexity of Teaching by Reinforcement on Q-Learning AAAI 2021 Adaptive Reward-Poisoning Attacks against Reinforcement Learning ICML 2020 Online Data Poisoning Attacks L4DC 2020 Task-agnostic Exploration in Reinforcement Learning NeurIPS 2020 An Optimal Control Approach to Sequential Machine Teaching AISTATS 2019 Policy Poisoning in Batch Reinforcement Learning and Control NeurIPS 2019 Teacher Improves Learning by Selecting a Training Subset AISTATS 2018