Safe and Efficient: A Primal-Dual Method for Offline Convex CMDPs under Partial Data Coverage.
NeurIPS 2024
Haobo Zhang, Xiyue Peng, Honghao Wei, and Xin Liu

Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning.
NeurIPS 2024
Honghao Wei, Xiyue Peng, Arnob Ghosh, and Xin Liu

Optimistic Joint Flow Control and Link Scheduling with Unknown Utility Functions.
MobiHoc 2024
Xin Liu, Honghao Wei, and Lei Ying

Stochastic Constrained Contextual Bandits via Lyapunov Optimization Based Estimation to Decision Framework.
COLT 2024
Hengquan Guo and Xin Liu

QueueFlower: Orchestration Microservice Workflows via Dynamic Queue Balancing.
ICWS 2024 (Short paper)
Hongchen Cao*, Xinrui Liu*, Hengquan Guo, Jingzhu He, and Xin Liu (*equal contribution)

Learning to Schedule Online Tasks with Bandit Feedback.
AAMAS 2024
Yongxin Xu, Shangshang Wang, Hengquan Guo, Xin Liu, and Ziyu Shao

Latency-Aware Microservice Deployment for Edge AI Enabled Video Analytics.
WCNC 2024
Zhanpeng Yang, Zhiyong Yu, Xin Liu, Dingzhu Wen, Yong Zhou, and Yuanming Shi

Safe Reinforcement Learning with Instantaneous Constraints: The Role of Aggressive Exploration.
AAAI 2024
Honghao Wei, Xin Liu, and Lei Ying

Sample Efficient Reinforcement Learning in Mixed Systems through Augmented Samples and Its Applications to Queueing Networks.
NeurIPS 2023 (Spotlight)
Honghao Wei, Xin Liu, Weina Wang, and Lei Ying

POBO: Safe and Optimal Resource Management for Cloud Microservices.
Performance 2023
Hengquan Guo*, Hongchen Cao*, Jingzhu He, Xin Liu, and Yuanming Shi (*equal contribution)

Federated Linear Bandit Learning via Over-the-air Computation.
GLOBECOM 2023
Jiali Wang, Yuning Jiang, Xin Liu, Ting Wang, and Yuanming Shi

Online Nonstochastic Control with Adversarial and Static Constraints .
ICML 2023
Xin Liu, Zixian Yang, and Lei Ying

Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-armed Bandit with Constraints.
L4DC 2023
Hengquan Guo, Qi Zhu, and Xin Liu

Neural Constrained Combinatorial Bandits.
INFOCOM 2023
Shangshang Wang, Simeng Bian, Xin Liu, and Ziyu Shao

Online Convex Optimization with Hard Constraints: Towards the Best of Two Worlds and Beyond.
NeurIPS 2022
Hengquan Guo, Xin Liu, Honghao Wei, and Lei Ying

Large-System Insensitivity of Zero-Waiting Load Balancing Algorithms.
Sigmetrics 2022
Xin Liu, Kang Gong, and Lei Ying

A Provably-Efficient Model-Free Algorithm for Constrained Markov Decision Processes.
AISTATS 2022 (A Short Version Accepted in ICML 2021 Workshop on Reinforcement Learning Theory)
Honghao Wei, Xin Liu, and Lei Ying

A Provably-Efficient Model-Free Algorithm for Infinite-Horizon Average-Reward Constrained Markov Decision Processes.
AAAI 2022
Honghao Wei, Xin Liu, and Lei Ying

An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints.
NeurIPS 2021
Xin Liu, Bin Li, Pengyi Shi, and Lei Ying

Beyond Scaling: Calculable Error Bounds of the Power-of-Two-Choices Mean-Field Model in Heavy-Traffic.
Mobihoc 2021
Hairi, Xin Liu, and Lei Ying

A Simple Steady-State Analysis of Load Balancing Algorithms in the Sub-Halfin-Whitt Regime.
Sigmetrics 2018 MAMA Workshop
Xin Liu and Lei Ying

On Achieving Zero Delay with Power-of-d-choices Load Balancing.
INFOCOM 2018. Fast-Track Review for IEEE TNSE (7 out of 312 accepted papers were invited at INFOCOM 2018)
Xin Liu and Lei Ying

Wireless Scheduling with Deadline and Power Constraints.
CISS 2018
Yiqiu Liu, Xin Liu, Lei Ying, and R. Srikant

Fluid-model-based Car Routing for Modern Ridesharing Systems.
Sigmetrics 2017 (Poster)
Anton Braverman, Jim Dai, Xin Liu, and Lei Ying

Spatial-temporal Routing for Supporting End-to-end Hard Deadlines in Multi-hop Networks.
CISS 2016
Xin Liu and Lei Ying

Probability Constrained Robust Multicast Beamforming in Cognitive Radio Network.
ChinaCom 2013. (Best Student Paper)
Xin Liu, Haoqi Li, and Haibin Wang

Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment.
Journal of Machine Learning Research, 2024
Zixian Yang, Xin Liu, and Lei Ying

Large-System Insensitivity of Zero-Waiting Load Balancing Algorithms.
Stochastic Systems, 2024
Xin Liu, Kang Gong, and Lei Ying

A Reinforcement Learning and Prediction-Based Lookahead Policy for Vehicle Repositioning in Online Ride-Hailing Systems.
IEEE Transactions on Intelligent Transportation Systems, 2023
Honghao Wei, Zixian Yang, Xin Liu, Zhiwei (Tony) Qin, Xiaocheng Tang, and Lei Ying

Federated Reinforcement Learning for Electric Vehicles Charging Control on Distribution Networks.
IEEE Internet of Things Journal, 2023
Junkai Qian, Yuning Jiang, Xin Liu, Qiong Wang, Ting Wang, Yuanming Shi, and Wei Chen

Universal Scaling of Distributed Queues Under Load Balancing in the Super-Halfin-Whitt Regime.
IEEE/ACM Transactions on Networking, 2022
Xin Liu and Lei Ying

Steady-State Analysis of Load Balancing with Coxian-2 Distribution Service Times.
Naval Research Logistics, Mar., 2021
Xin Liu, Kang Gong, and Lei Ying

Wireless Scheduling with Deadline and Power Constraints.
Performance Evaluation, Mar., 2021
Yiqiu Liu, Xin Liu, Lei Ying, and R. Srikant

Steady-State Analysis of Load Balancing Algorithms in the Sub-Halfin-Whitt Regime.
Journal of Applied Probability, Apr., 2020
Xin Liu and Lei Ying

On Achieving Zero Delay with Power-of-d-Choices Load Balancing.
IEEE Transactions on Network Science and Engineering. Oct., 2019
Xin Liu and Lei Ying

Empty-Car Routing in Ridesharing Systems.
Operations Research, Aug., 2019. Media coverage: [TechXplore] [Informs Press]
Anton Braverman, Jim Dai, Xin Liu, and Lei Ying

Spatial-Temporal Routing for Supporting End-to-End Hard Deadlines in Multi-Hop Networks.
Performance Evaluation, July, 2019
Xin Liu, Weichang Wang, and Lei Ying

Joint Beamforming and User Selection in Multicast Downlink Channel under Secrecy-outage Constraint.
IEEE Communications Letters , Jan., 2014
Xin Liu, Feifei Gao, Gongpu Wang, and Xiyuan Wang

Enhancing Safety in Reinforcement Learning with Human Feedback via Rectified Policy Optimization.
Xiyue Peng, Hengquan Guo, Jiawei Zhang, Dongqing Zou, Ziyu Shao, Honghao Wei, and Xin Liu

Scalable and Sample Efficient Distributed Policy Gradient Algorithms in Multi-Agent Networked Systems.
Xin Liu, Honghao Wei, and Lei Ying

POND: Pessimistic-Optimistic oNline Dispatching.
Invited to present in Sigmetrics 2021 RLNQ Workshop. It has been generalized to linear bandits and published in NeurIPS 2021.
Xin Liu, Bin Li, Pengyi Shi, and Lei Ying