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Zhengyuan Zhou

39 papers · 2013–2025 · 8 conferences · across top CS/AI conferences

Achievements

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+16 more ↓ πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (8)
🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) 🀝 Dynamic Duo (11) πŸ‘‘ Triple Crown πŸ† Grand Slam 🌱 Topic Pioneer πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (4) πŸ”₯ Unstoppable (9) ⚑ Prolific Year (6) ❓ The Questioner πŸ’Ž Century Club (39) πŸ—ƒοΈ Keyword Collector (128) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer

Conferences

ICML (14) NIPS (11) AISTATS (4) ICLR (3) JMLR (3) AAAI (2) COLT (1) L4DC (1)

Top co-authors

Jose Blanchet (11) Zijian Liu (7) Panayotis Mertikopoulos (6) Nicholas Bambos (6) Nian Si (4) Qinxun Bai (4) Maria Dimakopoulou (4) Perry Dong (3) Peter W. Glynn (3) Yi Ma (3)

Research topics

Reinforcement Learning (1)

Keywords

regret bound (9) distributionally robust optimization (4) game theory (4) online learning (4) nash equilibrium (4) multi-armed bandit (4) online algorithm (4) robust policy (4) sample complexity (3) reinforcement learning (3) contextual bandit (3) stochastic optimization (3) zero-sum game (3) multi-agent learning (3) regret analysis (2) non-convex optimization (2) stochastic gradient descent (2) offline reinforcement learning (2) convergence analysis (2) variance reduction (2)

Papers

Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization ICML 2025 Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping ICLR 2025 Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces AISTATS 2025 Concurrent Reinforcement Learning with Aggregated States via Randomized Least Squares Value Iteration ICML 2025 Distributionally Robust Policy Learning under Concept Drifts ICML 2025 Stochastic contextual bandits with graph feedback: from independence number to MAS number NIPS 2024 Sample Complexity of Variance-Reduced Distributionally Robust Q-Learning JMLR 2024 On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity ICML 2024 Adaptively Learning to Select-Rank in Online Platforms ICML 2024 On the Last-Iterate Convergence of Shuffling Gradient Methods ICML 2024 Feasible $Q$-Learning for Average Reward Reinforcement Learning AISTATS 2024 Single-Trajectory Distributionally Robust Reinforcement Learning ICML 2024 Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods ICLR 2024 A Finite Sample Complexity Bound for Distributionally Robust Q-learning AISTATS 2023 Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise COLT 2023 Society of Agents: Regret Bounds of Concurrent Thompson Sampling NIPS 2022 Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States JMLR 2022 Distributionally Robust $Q$-Learning ICML 2022 Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning ICML 2022 Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions NIPS 2022 No Weighted-Regret Learning in Adversarial Bandits with Delays JMLR 2022 Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems L4DC 2021 Online Multi-Armed Bandits with Adaptive Inference NIPS 2021 Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning AISTATS 2021 Delay-Adaptive Distributed Stochastic Optimization AAAI 2020 Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits ICML 2020 Gradient-free Online Learning in Continuous Games with Delayed Rewards ICML 2020 Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities NIPS 2020 Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games ICML 2020 Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness ICLR 2020 Balanced Linear Contextual Bandits AAAI 2019 Online EXP3 Learning in Adversarial Bandits with Delayed Feedback NIPS 2019 Learning in Generalized Linear Contextual Bandits with Stochastic Delays NIPS 2019 Learning in Games with Lossy Feedback NIPS 2018 MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels ICML 2018 Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? ICML 2018 Countering Feedback Delays in Multi-Agent Learning NIPS 2017 Stochastic Mirror Descent in Variationally Coherent Optimization Problems NIPS 2017 Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors NIPS 2013