Qiaomin Xie

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 74

Top Topics

Reinforcement Learning

Asymptotic Analysis

Nash Equilibrium

Top Venues

Math. Oper. Res.

Publications

Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie
Data Poisoning to Fake a Nash Equilibria for Markov Games. AAAI (2024)
Subhojyoti Mukherjee, Josiah P. Hanna, Qiaomin Xie, Robert D. Nowak
Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning. CoRR (2024)
Yiding Chen, Xuezhou Zhang, Qiaomin Xie, Xiaojin Zhu
Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption. AAAI (2024)
Jeremy McMahan, Giovanni Artiglio, Qiaomin Xie
Roping in Uncertainty: Robustness and Regularization in Markov Games. CoRR (2024)
Subhojyoti Mukherjee, Qiaomin Xie, Josiah P. Hanna, Robert D. Nowak
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits. AISTATS (2024)
Yixuan Zhang, Dongyan Lucy Huo, Yudong Chen, Qiaomin Xie
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA. SIGMETRICS/Performance (Abstracts) (2024)
Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie
Inception: Efficiently Computable Misinformation Attacks on Markov Games. CoRR (2024)
Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang
Unichain and Aperiodicity are Sufficient for Asymptotic Optimality of Average-Reward Restless Bandits. CoRR (2024)
Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang
When is exponential asymptotic optimality achievable in average-reward restless bandits? CoRR (2024)
Emmanouil-Vasileios Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, Qiaomin Xie
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements. AISTATS (2024)
Yixuan Zhang, Qiaomin Xie
Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation. CoRR (2024)
Jeremy McMahan, Young Wu, Xiaojin Zhu, Qiaomin Xie
Optimal Attack and Defense for Reinforcement Learning. AAAI (2024)
Dongyan Lucy Huo, Yudong Chen, Qiaomin Xie
Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference. AAAI (2024)
Yixuan Zhang, Dongyan Huo, Yudong Chen, Qiaomin Xie
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA. CoRR (2024)
Dongyan Huo, Yixuan Zhang, Yudong Chen, Qiaomin Xie
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize. CoRR (2024)
Yige Hong, Qiaomin Xie, Weina Wang
Near-Optimal Stochastic Bin-Packing in Large Service Systems with Time-Varying Item Sizes. SIGMETRICS/Performance (Abstracts) (2024)
Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert D. Nowak
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits. NeurIPS (2023)
Subhojyoti Mukherjee, Qiaomin Xie, Josiah P. Hanna, Robert D. Nowak
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits. CoRR (2023)
Xudong Qin, Qiaomin Xie, Bin Li
Distributed Threshold-Based Offloading for Heterogeneous Mobile Edge Computing. ICDCS (2023)
Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie
VISER: A Tractable Solution Concept for Games with Information Asymmetry. CoRR (2023)
Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Xiaojin Zhu, Qiaomin Xie
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value. CoRR (2023)
Dongyan Lucy Huo, Yudong Chen, Qiaomin Xie
Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes. SIGMETRICS (Abstracts) (2023)
Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie
Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning. AAAI (2023)
Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang
Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption. CoRR (2023)
Zihan Zhang, Qiaomin Xie
Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes. CoRR (2023)
Yige Hong, Qiaomin Xie, Weina Wang
Near-Optimal Stochastic Bin-Packing in Large Service Systems with Time-Varying Item Sizes. Proc. ACM Meas. Anal. Comput. Syst. 7 (3) (2023)
Zihan Zhang, Qiaomin Xie
Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes. COLT (2023)
Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie
On Faking a Nash Equilibrium. CoRR (2023)
Dongyan Huo, Yudong Chen, Qiaomin Xie
Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference. CoRR (2023)
Emmanouil-Vasileios Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, Qiaomin Xie
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements. CoRR (2023)
Jeremy McMahan, Young Wu, Xiaojin Zhu, Qiaomin Xie
Optimal Attack and Defense for Reinforcement Learning. CoRR (2023)
Brahma S. Pavse, Yudong Chen, Qiaomin Xie, Josiah P. Hanna
Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning. CoRR (2023)
Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, Robert D. Nowak
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits. CoRR (2023)
Peihan Huo, Oscar Peralta, Junyu Guo, Qiaomin Xie, Andreea Minca
Reinforcement Learning for SBM Graphon Games with Re-Sampling. CoRR (2023)
Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang
Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption. NeurIPS (2023)
Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. Math. Oper. Res. 48 (1) (2023)
Yige Hong, Qiaomin Xie, Weina Wang
Maximizing Utilization under Time-Varying Resource Requirements. CoRR (2022)
Bai Liu, Qiaomin Xie, Eytan H. Modiano
RL-QN: A Reinforcement Learning Framework for Optimal Control of Queueing Systems. ACM Trans. Model. Perform. Evaluation Comput. Syst. 7 (1) (2022)
Dongyan Huo, Yudong Chen, Qiaomin Xie
Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes. CoRR (2022)
Christopher Archer, Siddhartha Banerjee, Mayleen Cortez, Carrie Rucker, Sean R. Sinclair, Max Solberg, Qiaomin Xie, Christina Lee Yu
ORSuite: Benchmarking Suite for Sequential Operations Models. SIGMETRICS Perform. Evaluation Rev. 49 (2) (2022)
Devavrat Shah, Qiaomin Xie, Zhi Xu
Nonasymptotic Analysis of Monte Carlo Tree Search. Oper. Res. 70 (6) (2022)
Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie
Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning. CoRR (2022)
Varun Gupta, Benjamin Moseley, Marc Uetz, Qiaomin Xie
Corrigendum: Greed Works - Online Algorithms for Unrelated Machine Stochastic Scheduling. Math. Oper. Res. 46 (3) (2021)
Weina Wang, Qiaomin Xie, Mor Harchol-Balter
Zero Queueing for Multi-Server Jobs. SIGMETRICS (Abstracts) (2021)
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
Learning While Playing in Mean-Field Games: Convergence and Optimality. ICML (2021)
Weina Wang, Qiaomin Xie, Mor Harchol-Balter
Zero Queueing for Multi-Server Jobs. Proc. ACM Meas. Anal. Comput. Syst. 5 (1) (2021)
Bai Liu, Qiaomin Xie, Eytan H. Modiano
RL-QN: A Reinforcement Learning Framework for Optimal Control of Queueing Systems. CoRR (2020)
Yingjie Fei, Zhuoran Yang, Zhaoran Wang, Qiaomin Xie
Dynamic Regret of Policy Optimization in Non-Stationary Environments. NeurIPS (2020)
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
Provable Fictitious Play for General Mean-Field Games. CoRR (2020)
Yingjie Fei, Zhuoran Yang, Zhaoran Wang, Qiaomin Xie
Dynamic Regret of Policy Optimization in Non-stationary Environments. CoRR (2020)
Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. COLT (2020)
Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis. NeurIPS (2020)
Devavrat Shah, Qiaomin Xie, Zhi Xu
Stable Reinforcement Learning with Unbounded State Space. L4DC (2020)
Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis. CoRR (2020)
Weina Wang, Qiaomin Xie, Mor Harchol-Balter
Zero Queueing for Multi-Server Jobs. CoRR (2020)
Devavrat Shah, Varun Somani, Qiaomin Xie, Zhi Xu
On Reinforcement Learning for Turn-based Zero-sum Markov Games. CoRR (2020)
Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret. CoRR (2020)
Devavrat Shah, Qiaomin Xie, Zhi Xu
Stable Reinforcement Learning with Unbounded State Space. CoRR (2020)
Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret. NeurIPS (2020)
Varun Gupta, Benjamin Moseley, Marc Uetz, Qiaomin Xie
Greed Works - Online Algorithms for Unrelated Machine Stochastic Scheduling. Math. Oper. Res. 45 (2) (2020)
Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. CoRR (2020)
Devavrat Shah, Varun Somani, Qiaomin Xie, Zhi Xu
On Reinforcement Learning for Turn-based Zero-sum Markov Games. FODS (2020)
Devavrat Shah, Qiaomin Xie, Zhi Xu
Non-Asymptotic Analysis of Monte Carlo Tree Search. SIGMETRICS (Abstracts) (2020)
Devavrat Shah, Qiaomin Xie, Zhi Xu
On Reinforcement Learning Using Monte Carlo Tree Search with Supervised Learning: Non-Asymptotic Analysis. CoRR (2019)
Bai Liu, Qiaomin Xie, Eytan H. Modiano
Reinforcement Learning for Optimal Control of Queueing Systems. Allerton (2019)
Devavrat Shah, Qiaomin Xie
Q-learning with Nearest Neighbors. CoRR (2018)
Devavrat Shah, Qiaomin Xie
Q-learning with Nearest Neighbors. NeurIPS (2018)
Varun Gupta, Benjamin Moseley, Marc Uetz, Qiaomin Xie
Stochastic Online Scheduling on Unrelated Machines. IPCO (2017)
Varun Gupta, Benjamin Moseley, Marc Uetz, Qiaomin Xie
Stochastic Online Scheduling on Unrelated Machines. CoRR (2017)
Devavrat Shah, Qiaomin Xie
Centralized Congestion Control and Scheduling in a Datacenter. CoRR (2017)
Qiaomin Xie, Mayank Pundir, Yi Lu, Cristina L. Abad, Roy H. Campbell
Pandas: Robust Locality-Aware Scheduling With Stochastic Delay Optimality. IEEE/ACM Trans. Netw. 25 (2) (2017)
Qiaomin Xie, Ali Yekkehkhany, Yi Lu
Scheduling with multi-level data locality: Throughput and heavy-traffic optimality. INFOCOM (2016)
Qiaomin Xie, Xiaobo Dong, Yi Lu, Rayadurgam Srikant
Choices for Large-Scale Bin Packing: A Loss Model. SIGMETRICS (2015)
Qiaomin Xie, Yi Lu
Priority algorithm for near-data scheduling: Throughput and heavy-traffic optimality. INFOCOM (2015)
Qiaomin Xie, Yi Lu
Degree-guided map-reduce task assignment with data locality constraint. ISIT (2012)
Yi Lu, Qiaomin Xie, Gabriel Kliot, Alan Geller, James R. Larus, Albert G. Greenberg
Join-Idle-Queue: A novel load balancing algorithm for dynamically scalable web services. Perform. Evaluation 68 (11) (2011)