Join-Idle-Queue: A novel load balancing algorithm for dynamically scalable web services. - Yi Lu 001; Qiaomin Xie; Gabriel Kliot; Alan Geller; James R. Larus; Albert G. Greenberg (Perform. Evaluation, 2011)

Degree-guided map-reduce task assignment with data locality constraint. - Qiaomin Xie; Yi Lu 001 (ISIT, 2012)

Priority algorithm for near-data scheduling: Throughput and heavy-traffic optimality. - Qiaomin Xie; Yi Lu 001 (INFOCOM, 2015)

Power of d Choices for Large-Scale Bin Packing: A Loss Model. - Qiaomin Xie; Xiaobo Dong; Yi Lu 001; Rayadurgam Srikant (SIGMETRICS, 2015)

Scheduling with multi-level data locality: Throughput and heavy-traffic optimality. - Qiaomin Xie; Ali Yekkehkhany; Yi Lu 001 (INFOCOM, 2016)

Scheduling and resource allocation for clouds: novel algorithms, state space collapse and decay of tails - Qiaomin Xie (2016)

Stochastic Online Scheduling on Unrelated Machines. - Varun Gupta 004; Benjamin Moseley; Marc Uetz; Qiaomin Xie (IPCO, 2017)

Centralized Congestion Control and Scheduling in a Datacenter. - Devavrat Shah; Qiaomin Xie (CoRR, 2017)

Pandas: Robust Locality-Aware Scheduling With Stochastic Delay Optimality. - Qiaomin Xie; Mayank Pundir; Yi Lu 001; Cristina L. Abad; Roy H. Campbell (IEEE/ACM Trans. Netw., 2017)

Q-learning with Nearest Neighbors. - Devavrat Shah; Qiaomin Xie (NeurIPS, 2018)

Reinforcement Learning for Optimal Control of Queueing Systems. - Bai Liu; Qiaomin Xie; Eytan H. Modiano (Allerton, 2019)

On Reinforcement Learning Using Monte Carlo Tree Search with Supervised Learning: Non-Asymptotic Analysis. - Devavrat Shah; Qiaomin Xie; Zhi Xu 001 (CoRR, 2019)

On Reinforcement Learning for Turn-based Zero-sum Markov Games. - Devavrat Shah; Varun Somani; Qiaomin Xie; Zhi Xu 001 (FODS, 2020)

Stable Reinforcement Learning with Unbounded State Space. - Devavrat Shah; Qiaomin Xie; Zhi Xu 001 (L4DC, 2020)

Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret. - Yingjie Fei; Zhuoran Yang; Yudong Chen 001; Zhaoran Wang 001; Qiaomin Xie (NeurIPS, 2020)

Dynamic Regret of Policy Optimization in Non-Stationary Environments. - Yingjie Fei; Zhuoran Yang; Zhaoran Wang 001; Qiaomin Xie (NeurIPS, 2020)

POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis. - Weichao Mao; Kaiqing Zhang; Qiaomin Xie; Tamer Basar (NeurIPS, 2020)

Non-Asymptotic Analysis of Monte Carlo Tree Search. - Devavrat Shah; Qiaomin Xie; Zhi Xu 001 (SIGMETRICS (Abstracts), 2020)

Provable Fictitious Play for General Mean-Field Games. - Qiaomin Xie; Zhuoran Yang; Zhaoran Wang 001; Andreea Minca (CoRR, 2020)

Greed Works - Online Algorithms for Unrelated Machine Stochastic Scheduling. - Varun Gupta 004; Benjamin Moseley; Marc Uetz; Qiaomin Xie (Math. Oper. Res., 2020)

Learning While Playing in Mean-Field Games: Convergence and Optimality. - Qiaomin Xie; Zhuoran Yang; Zhaoran Wang 001; Andreea Minca (ICML, 2021)

Corrigendum: Greed Works - Online Algorithms for Unrelated Machine Stochastic Scheduling. - Varun Gupta 004; Benjamin Moseley; Marc Uetz; Qiaomin Xie (Math. Oper. Res., 2021)

Zero Queueing for Multi-Server Jobs. - Weina Wang 001; Qiaomin Xie; Mor Harchol-Balter (Proc. ACM Meas. Anal. Comput. Syst., 2021)

Maximizing Utilization under Time-Varying Resource Requirements. - Yige Hong; Qiaomin Xie; Weina Wang 001 (CoRR, 2022)

ORSuite: Benchmarking Suite for Sequential Operations Models. - Christopher Archer; Siddhartha Banerjee; Mayleen Cortez; Carrie Rucker; Sean R. Sinclair; Max Solberg; Qiaomin Xie; Christina Lee Yu (SIGMETRICS Perform. Evaluation Rev., 2022)

RL-QN: A Reinforcement Learning Framework for Optimal Control of Queueing Systems. - Bai Liu; Qiaomin Xie; Eytan H. Modiano (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2022)

Nonasymptotic Analysis of Monte Carlo Tree Search. - Devavrat Shah; Qiaomin Xie; Zhi Xu 001 (Oper. Res., 2022)

Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning. - Young Wu; Jeremy McMahan; Xiaojin Zhu 001; Qiaomin Xie (AAAI, 2023)

Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes. - Zihan Zhang; Qiaomin Xie (COLT, 2023)

Distributed Threshold-Based Offloading for Heterogeneous Mobile Edge Computing. - Xudong Qin; Qiaomin Xie; Bin Li 014 (ICDCS, 2023)

Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption. - Yige Hong; Qiaomin Xie; Yudong Chen 001; Weina Wang 001 (NeurIPS, 2023)

Multi-task Representation Learning for Pure Exploration in Bilinear Bandits. - Subhojyoti Mukherjee; Qiaomin Xie; Josiah Hanna; Robert D. Nowak (NeurIPS, 2023)

Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes. - Dongyan Lucy Huo; Yudong Chen 001; Qiaomin Xie (SIGMETRICS (Abstracts), 2023)

Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning. - Brahma S. Pavse; Yudong Chen 001; Qiaomin Xie; Josiah P. Hanna (CoRR, 2023)

On Faking a Nash Equilibrium. - Young Wu; Jeremy McMahan; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2023)

VISER: A Tractable Solution Concept for Games with Information Asymmetry. - Jeremy McMahan; Young Wu; Yudong Chen 001; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2023)

Reinforcement Learning for SBM Graphon Games with Re-Sampling. - Peihan Huo; Oscar Peralta; Junyu Guo; Qiaomin Xie; Andreea Minca (CoRR, 2023)

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value. - Young Wu; Jeremy McMahan; Yiding Chen; Yudong Chen 001; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2023)

Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. - Qiaomin Xie; Yudong Chen 001; Zhaoran Wang 001; Zhuoran Yang (Math. Oper. Res., 2023)

Near-Optimal Stochastic Bin-Packing in Large Service Systems with Time-Varying Item Sizes. - Yige Hong; Qiaomin Xie; Weina Wang 001 (Proc. ACM Meas. Anal. Comput. Syst., 2023)

Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption. - Yiding Chen; Xuezhou Zhang; Qiaomin Xie; Xiaojin Zhu 001 (AAAI, 2024)

Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference. - Dongyan Lucy Huo; Yudong Chen 001; Qiaomin Xie (AAAI, 2024)

Optimal Attack and Defense for Reinforcement Learning. - Jeremy McMahan; Young Wu; Xiaojin Zhu 001; Qiaomin Xie (AAAI, 2024)

Data Poisoning to Fake a Nash Equilibria for Markov Games. - Young Wu; Jeremy McMahan; Xiaojin Zhu 001; Qiaomin Xie (AAAI, 2024)

SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits. - Subhojyoti Mukherjee; Qiaomin Xie; Josiah P. Hanna; Robert D. Nowak (AISTATS, 2024)

Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements. - Emmanouil-Vasileios Vlatakis-Gkaragkounis; Angeliki Giannou; Yudong Chen 001; Qiaomin Xie (AISTATS, 2024)

Roping in Uncertainty: Robustness and Regularization in Markov Games. - Jeremy McMahan; Giovanni Artiglio; Qiaomin Xie (ICML, 2024)

Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces. - Brahma S. Pavse; Matthew Zurek; Yudong Chen 001; Qiaomin Xie; Josiah P. Hanna (ICML, 2024)

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value. - Young Wu; Jeremy McMahan; Yiding Chen; Yudong Chen 001; Jerry Zhu; Qiaomin Xie (ICML, 2024)

The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize. - Dongyan Lucy Huo; Yixuan Zhang; Yudong Chen 001; Qiaomin Xie (NeurIPS, 2024)

Inception: Efficiently Computable Misinformation Attacks on Markov Games. - Jeremy McMahan; Young Wu; Yudong Chen 001; Jerry Zhu; Qiaomin Xie (RLJ, 2024)

Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation. - Yixuan Zhang; Qiaomin Xie (RLJ, 2024)

Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA. - Yixuan Zhang; Dongyan Lucy Huo; Yudong Chen 001; Qiaomin Xie (SIGMETRICS/Performance (Abstracts), 2024)

Unichain and Aperiodicity are Sufficient for Asymptotic Optimality of Average-Reward Restless Bandits. - Yige Hong; Qiaomin Xie; Yudong Chen 001; Weina Wang 001 (CoRR, 2024)

When is exponential asymptotic optimality achievable in average-reward restless bandits? - Yige Hong; Qiaomin Xie; Yudong Chen 001; Weina Wang 001 (CoRR, 2024)

Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning. - Subhojyoti Mukherjee; Josiah P. Hanna; Qiaomin Xie; Robert D. Nowak (CoRR, 2024)

Inception: Efficiently Computable Misinformation Attacks on Markov Games. - Jeremy McMahan; Young Wu; Yudong Chen 001; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2024)

Stable Offline Value Function Learning with Bisimulation-based Representations. - Brahma S. Pavse; Yudong Chen 001; Qiaomin Xie; Josiah P. Hanna (CoRR, 2024)

Coupling-based Convergence Diagnostic and Stepsize Scheme for Stochastic Gradient Descent. - Xiang Li; Qiaomin Xie (AAAI, 2025)

Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way. - Jeongyeol Kwon; Luke Dotson; Yudong Chen 001; Qiaomin Xie (AISTATS, 2025)

A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression. - Yixuan Zhang; Dongyan Lucy Huo; Yudong Chen 001; Qiaomin Xie (SIGMETRICS (Abstracts), 2025)

Optimally Installing Strict Equilibria. - Jeremy McMahan; Young Wu; Yudong Chen 001; Xiaojin Zhu 001; Qiaomin Xie (CoRR, 2025)

Contextual Online Pricing with (Biased) Offline Data. - Yixuan Zhang; Ruihao Zhu; Qiaomin Xie (CoRR, 2025)