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Zhengyuan Zhou

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

Achievements

πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (3) πŸƒ Academic Marathon (12) 🌈 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