Qiaomin Xie
25 papers · 2018–2026 · 6 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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(6)
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(10)
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(133)
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Research topics
Machine Learning
(18)
Reinforcement Learning
(17)
Methods
(15)
Optimization & Theory Β· Machine Learning
(14)
Mathematics & Optimization
(12)
Learning Types
(11)
Optimization
(10)
Artificial Intelligence
(6)
Core AI
(6)
Applications
(4)
Deep Learning
(2)
Optimization & Theory Β· Deep Learning
(2)
Probability
(2)
Robotics
(1)
Application Areas
(1)
Keywords
markov decision process
(6)
markov chain
(6)
sample complexity
(5)
regret bound
(4)
constant step size
(4)
reinforcement learning
(4)
nash equilibrium
(4)
markov game
(3)
multi-agent system
(3)
policy optimization
(3)
restless bandit
(2)
model-free reinforcement learning
(2)
queueing network
(2)
online training
(2)
adversarial attack
(2)
stochastic approximation
(2)
multi-armed bandit
(2)
offline reinforcement learning
(2)
stochastic optimization
(2)
experimental design
(2)
Papers
Lyapunov-Based Sample Complexity Analysis for Weakly-Coupled MDPs (extended abstract)
COLT 2026
Coupling-based Convergence Diagnostic and Stepsize Scheme for Stochastic Gradient Descent
AAAI 2025
Stable Offline Value Function Learning with Bisimulation-based Representations
ICML 2025
Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way
AISTATS 2025
Data Poisoning to Fake a Nash Equilibria for Markov Games
AAAI 2024
Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference
AAAI 2024
Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption
AAAI 2024
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
ICML 2024
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value
ICML 2024
Optimal Attack and Defense for Reinforcement Learning
AAAI 2024
Roping in Uncertainty: Robustness and Regularization in Markov Games
ICML 2024
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits
AISTATS 2024
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
AISTATS 2024
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
NeurIPS 2024
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
NeurIPS 2023
Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption
NeurIPS 2023
Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning
AAAI 2023
Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes
COLT 2023
Learning While Playing in Mean-Field Games: Convergence and Optimality
ICML 2021
Dynamic Regret of Policy Optimization in Non-Stationary Environments
NeurIPS 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium
COLT 2020
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
NeurIPS 2020
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
NeurIPS 2020
Stable Reinforcement Learning with Unbounded State Space
L4DC 2020
Q-learning with Nearest Neighbors
NeurIPS 2018