Publications

publications in reversed chronological order.

  1. Near-Optimal Stochastic Bin-Packing in Large Service Systems with Time-Varying Item Sizes
    Yige Hong, Qiaomin Xie, and Weina Wang
    In ACM Sigmetrics 2024
  2. SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits
    Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, and Robert Nowak
    In International Conference on Artificial Intelligence and Statistics (AISTATS) 2024
  3. Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
    Emmanouil-Vasileios Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, and Qiaomin Xie
    In International Conference on Artificial Intelligence and Statistics (AISTATS), Oral 2024
  4. Data Poisoning to Fake a Nash Equilibrium in Markov Games
    Young Wu, Jeremy McMahan, Xiaojin Zhu, and Qiaomin Xie
    In AAAI Conference on Artificial Intelligence 2024
  5. Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference
    Dongyan Huo, Yudong Chen, and Qiaomin Xie
    In AAAI Conference on Artificial Intelligence 2024
  6. Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption
    Yiding Chen, Xuezhou Zhang, Qiaomin Xie, and Xiaojin Zhu
    In AAAI Conference on Artificial Intelligence 2024
  7. Optimal Attack and Defense for Reinforcement Learning
    Jeremy McMahan, Young Wu, Xiaojin Zhu, and Qiaomin Xie
    In AAAI Conference on Artificial Intelligence 2024
  8. Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
    Subhojyoti Mukherjee, Qiaomin Xie, Josiah Hanna, and Robert Nowak
    In Advances in Neural Information Processing Systems (NeurIPS) 2023
  9. Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption
    Yige Hong, Qiaomin Xie, Yudong Chen, and Weina Wang
    In Advances in Neural Information Processing Systems (NeurIPS), Spotlight, 2023
  10. Distributed Threshold-based Offloading for Heterogeneous Mobile Edge Computing
    Xudong Qin, Qiaomin Xie, and Bin Li
    In International Conference on Distributed Computing Systems (ICDCS) 2023
  11. Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes
    Zihan Zhang, and Qiaomin Xie
    In Conference on Learning Theory (COLT) 2023
  12. Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes
    Dongyan Huo, Yudong Chen, and Qiaomin Xie
    In ACM Sigmetrics 2023
  13. Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium
    Qiaomin Xie, Yudong Chen, Zhaoran Wang, and Zhuoran Yang
    Mathematics of Operations Research 2023
  14. Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning
    Young Wu, Jermey McMahan, Xiaojin Zhu, and Qiaomin Xie
    In AAAI Conference on Artificial Intelligence 2023
  15. Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning
    Brahma S. Pavse, Yudong Chen, Qiaomin Xie, and Josiah P. Hanna
    arXiv preprint arXiv:2306.01896 2023
  16. RL-QN: A Reinforcement Learning Framework for Optimal Control of Queueing Systems
    Bai Liu, Qiaomin Xie, and Eytan Modiano
    ACM Transactions on Modeling and Performance Evaluation of Computing Systems 2022
  17. ORSuite: Benchmarking Suite for Sequential Operations Models
    Christopher Archer, Siddhartha Banerjee, Mayleen Cortez, Carrie Rucker, Sean R. Sinclair, Max Solberg, Qiaomin Xie, and Christina Lee Yu
    SIGMETRICS Performance Evaluation Review 2022
  18. Nonasymptotic Analysis of Monte Carlo Tree Search
    Devavrat Shah, Qiaomin Xie, and Zhi Xu
    Operations Research 2022
  19. Learning While Playing in Mean-Field Games: Convergence and Optimality
    Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, and Andreea Minca
    In International Conference on Machine Learning (ICML) 2021
  20. Zero queueing for multi-server jobs
    Weina Wang, Qiaomin Xie, and Mor Harchol-Balter
    In ACM Sigmetrics 2021
  21. Dynamic Regret of Policy Optimization in Non-Stationary Environments
    Yingjie Fei, Zhuoran Yang, Zhaoran Wang, and Qiaomin Xie
    In Advances in Neural Information Processing Systems (NeurIPS) 2020
  22. POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
    Weichao Mao, Kaiqing Zhang, Qiaomin Xie, and Tamer Basar
    In Advances in Neural Information Processing Systems (NeurIPS) 2020
  23. Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
    Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, and Qiaomin Xie
    In Advances in Neural Information Processing Systems (NeurIPS) 2020
  24. Stable Reinforcement Learning with Unbounded State Space
    Devavrat Shah, Qiaomin Xie, and Zhi Xu
    In Learning for Dynamics and Control (L4DC) 2020
  25. On Reinforcement Learning for Turn-based Zero-sum Markov Games
    Devavrat Shah, Varun Somani, Qiaomin Xie, and Zhi Xu
    In Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference 2020
  26. Learning zero-sum simultaneous-move Markov games using function approximation and correlated equilibrium
    Qiaomin Xie, Yudong Chen, Zhaoran Wang, and Zhuoran Yang
    In Conference on Learning Theory 2020
  27. Non-asymptotic analysis of Monte Carlo tree search
    Devavrat Shah, Qiaomin Xie, and Zhi Xu
    In ACM Sigmetrics 2020
  28. Greed works—online algorithms for unrelated machine stochastic scheduling
    Varun Gupta, Benjamin Moseley, Marc Uetz, and Qiaomin Xie
    Mathematics of operations research 2020
  29. Reinforcement learning for optimal control of queueing systems
    Bai Liu, Qiaomin Xie, and Eytan Modiano
    In 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton) 2019
  30. Q-learning with nearest neighbors
    Devavrat Shah, and Qiaomin Xie
    In Advances in Neural Information Processing Systems (NeurIPS) 2018
  31. Stochastic online scheduling on unrelated machines
    Varun Gupta, Benjamin Moseley, Marc Uetz, and Qiaomin Xie
    In International Conference on Integer Programming and Combinatorial Optimization 2017
  32. Centralized Congestion Control and Scheduling in a Datacenter
    Devavrat Shah, and Qiaomin Xie
    arXiv preprint arXiv:1710.02548 2017
  33. Scheduling with Multi-level Data Locality: Throughput and Heavy-Traffic Optimality
    Qiaomin Xie, Ali Yekkehkhany, and Yi Lu
    In 2016 IEEE Conference on Computer Communications (INFOCOM) 2016
  34. Pandas: robust locality-aware scheduling with stochastic delay optimality
    Qiaomin Xie, Mayank Pundir, Yi Lu, Cristina L Abad, and Roy H Campbell
    IEEE/ACM Transactions on Networking 2016
  35. Power of d Choices for Large-Scale Bin Packing: A Loss Model
    Qiaomin Xie, Xiaobo Dong, Yi Lu, and R Srikant
    In ACM Sigmetrics 2015
  36. Priority algorithm for near-data scheduling: Throughput and heavy-traffic optimality
    Qiaomin Xie, and Yi Lu
    In 2015 IEEE Conference on Computer Communications (INFOCOM) 2015
  37. Degree-guided map-reduce task assignment with data locality constraint
    Qiaomin Xie, and Yi Lu
    In 2012 IEEE International Symposium on Information Theory Proceedings 2012
  38. Join-idle-queue: A novel load balancing algorithm for dynamically scalable web services
    Yi Lu, Qiaomin Xie, Gabriel Kliot, Alan Geller, James R Larus, and Albert Greenberg
    Performance Evaluation 2011