Qiaomin Xie
24 papers · 2018–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (7) π§ Keyword Pioneer π Conference Polyglot (6) π Interdisciplinary Bridge π Cross-Pollinator (12)
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Cross-Pollinator
(12)
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Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(40)
π§¬
Topic Evolution
π
Keyword Champion
(6)
π±
Topic Pioneer
π€
Dynamic Duo
(10)
π
Century Club
(24)
ποΈ
Keyword Collector
(107)
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Trend Setter
β‘
Prolific Year
(5)
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Conference Pioneer
Conferences
NIPS (7)
AAAI (6)
ICML (5)
AISTATS (3)
COLT (2)
L4DC (1)
Top co-authors
Research topics
Keywords
markov chain
(6)
regret bound
(4)
markov decision process
(4)
sample complexity
(4)
reinforcement learning
(4)
policy optimization
(3)
multi-agent system
(3)
nash equilibrium
(2)
constant stepsize
(2)
multi-armed bandit
(2)
stochastic optimization
(2)
adversarial attack
(2)
offline reinforcement learning
(2)
experimental design
(2)
model-free reinforcement learning
(2)
function approximation
(1)
variational inequality
(1)
policy evaluation
(1)
game theory
(1)
multi-task learning
(1)
Papers
Stable Offline Value Function Learning with Bisimulation-based Representations
ICML 2025
Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way
AISTATS 2025
Coupling-based Convergence Diagnostic and Stepsize Scheme for Stochastic Gradient Descent
AAAI 2025
Roping in Uncertainty: Robustness and Regularization in Markov Games
ICML 2024
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits
AISTATS 2024
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
ICML 2024
Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption
AAAI 2024
Optimal Attack and Defense for Reinforcement Learning
AAAI 2024
Data Poisoning to Fake a Nash Equilibria for Markov Games
AAAI 2024
Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference
AAAI 2024
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
NIPS 2024
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
AISTATS 2024
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value
ICML 2024
Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes
COLT 2023
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
NIPS 2023
Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning
AAAI 2023
Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption
NIPS 2023
Learning While Playing in Mean-Field Games: Convergence and Optimality
ICML 2021
Stable Reinforcement Learning with Unbounded State Space
L4DC 2020
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
NIPS 2020
Dynamic Regret of Policy Optimization in Non-Stationary Environments
NIPS 2020
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
NIPS 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium
COLT 2020
Q-learning with Nearest Neighbors
NIPS 2018