Qiaomin Xie

Proceedings of the 1st Reinforcement Learning Conference, 2024

Inception: Efficiently Computable Misinformation Attacks on Markov Games.

[BibT_eX]

Proceedings of the 1st Reinforcement Learning Conference, 2024

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Roping in Uncertainty: Robustness and Regularization in Markov Games.

[BibT_eX]

[DOI]

Jeremy McMahan

Giovanni Artiglio

Emmanouil-Vasileios Vlatakis-Gkaragkounis

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements.

[BibT_eX]

[DOI]

Angeliki Giannou

Yudong Chen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Data Poisoning to Fake a Nash Equilibria for Markov Games.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Optimal Attack and Defense for Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference.

[BibT_eX]

[DOI]

Dongyan Lucy Huo

Yudong Chen

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Near-Optimal Stochastic Bin-Packing in Large Service Systems with Time-Varying Item Sizes.

[BibT_eX]

[DOI]

Yige Hong

Weina Wang

Proc. ACM Meas. Anal. Comput. Syst., December, 2023

Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium.

[BibT_eX]

[DOI]

Math. Oper. Res., February, 2023

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value.

[BibT_eX]

[DOI]

CoRR, 2023

Reinforcement Learning for SBM Graphon Games with Re-Sampling.

[BibT_eX]

[DOI]

CoRR, 2023

VISER: A Tractable Solution Concept for Games with Information Asymmetry.

[BibT_eX]

[DOI]

CoRR, 2023

On Faking a Nash Equilibrium.

[BibT_eX]

[DOI]

CoRR, 2023

Tackling Unbounded State Spaces in Continuing Task Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes.

[BibT_eX]

[DOI]

Dongyan Lucy Huo

Yudong Chen

Proceedings of the Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2023

Multi-task Representation Learning for Pure Exploration in Bilinear Bandits.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distributed Threshold-Based Offloading for Heterogeneous Mobile Edge Computing.

[BibT_eX]

[DOI]

Xudong Qin

Bin Li

Proceedings of the 43rd IEEE International Conference on Distributed Computing Systems, 2023

Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes.

[BibT_eX]

[DOI]

Zihan Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Nonasymptotic Analysis of Monte Carlo Tree Search.

[BibT_eX]

[DOI]

Oper. Res., November, 2022

RL-QN: A Reinforcement Learning Framework for Optimal Control of Queueing Systems.

[BibT_eX]

[DOI]

Bai Liu

Eytan H. Modiano

ACM Trans. Model. Perform. Evaluation Comput. Syst., 2022

ORSuite: Benchmarking Suite for Sequential Operations Models.

[BibT_eX]

[DOI]

SIGMETRICS Perform. Evaluation Rev., 2022

Maximizing Utilization under Time-Varying Resource Requirements.

[BibT_eX]

[DOI]

Yige Hong

Weina Wang

CoRR, 2022

2021

Zero Queueing for Multi-Server Jobs.

[BibT_eX]

[DOI]

Weina Wang

Mor Harchol-Balter

Proc. ACM Meas. Anal. Comput. Syst., 2021

Corrigendum: Greed Works - Online Algorithms for Unrelated Machine Stochastic Scheduling.

[BibT_eX]

[DOI]

Math. Oper. Res., 2021

Learning While Playing in Mean-Field Games: Convergence and Optimality.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Greed Works - Online Algorithms for Unrelated Machine Stochastic Scheduling.

[BibT_eX]

[DOI]

Math. Oper. Res., 2020

Provable Fictitious Play for General Mean-Field Games.

[BibT_eX]

[DOI]

CoRR, 2020

Non-Asymptotic Analysis of Monte Carlo Tree Search.

[BibT_eX]

[DOI]

Proceedings of the Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems, 2020

POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Dynamic Regret of Policy Optimization in Non-Stationary Environments.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stable Reinforcement Learning with Unbounded State Space.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

On Reinforcement Learning for Turn-based Zero-sum Markov Games.

[BibT_eX]

[DOI]

Proceedings of the FODS '20: ACM-IMS Foundations of Data Science Conference, 2020

2019

On Reinforcement Learning Using Monte Carlo Tree Search with Supervised Learning: Non-Asymptotic Analysis.

[BibT_eX]

[DOI]

CoRR, 2019

Reinforcement Learning for Optimal Control of Queueing Systems.

[BibT_eX]

[DOI]

Bai Liu

Eytan H. Modiano

Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018

Q-learning with Nearest Neighbors.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Pandas: Robust Locality-Aware Scheduling With Stochastic Delay Optimality.

[BibT_eX]

[DOI]

IEEE/ACM Trans. Netw., 2017

Centralized Congestion Control and Scheduling in a Datacenter.

[BibT_eX]

[DOI]

CoRR, 2017

Stochastic Online Scheduling on Unrelated Machines.

[BibT_eX]

[DOI]

Proceedings of the Integer Programming and Combinatorial Optimization, 2017

2016

Scheduling and resource allocation for clouds: novel algorithms, state space collapse and decay of tails

[BibT_eX]

[DOI]

PhD thesis, 2016

Scheduling with multi-level data locality: Throughput and heavy-traffic optimality.

[BibT_eX]

[DOI]

Ali Yekkehkhany

Yi Lu

Proceedings of the 35th Annual IEEE International Conference on Computer Communications, 2016

2015

Power of <i>d</i> Choices for Large-Scale Bin Packing: A Loss Model.

[BibT_eX]

[DOI]

Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015

Priority algorithm for near-data scheduling: Throughput and heavy-traffic optimality.

[BibT_eX]

[DOI]

Yi Lu

Proceedings of the 2015 IEEE Conference on Computer Communications, 2015

2012

Degree-guided map-reduce task assignment with data locality constraint.

[BibT_eX]

[DOI]