Online Pricing for Revenue Maximization with Unknown Time Discounting Valuations. - Weichao Mao; Zhenzhe Zheng; Fan Wu 006; Guihai Chen (IJCAI, 2018)

Adjusting Matching Algorithm to Adapt to Dynamic Subscriptions in Content-Based Publish/Subscribe Systems. - Weichao Mao; Jian Cao 001; Guangtao Xue; Jiadi Yu; Yanmin Zhu 006; Minglu Li 001; Wenjuan Li 002; Shiyou Qian (ISPA/IUCC/BDCloud/SocialCom/SustainCom, 2018)

Challenges and Opportunities in IoT Data Markets. - Zhenzhe Zheng; Weichao Mao; Fan Wu 006; Guihai Chen (SocialSens@CPSIoTWeek, 2019)

Pricing for Revenue Maximization in IoT Data Markets: An Information Design Perspective. - Weichao Mao; Zhenzhe Zheng; Fan Wu 006 (INFOCOM, 2019)

Adjusting Matching Algorithm to Adapt to Workload Fluctuations in Content-based Publish/Subscribe Systems. - Shiyou Qian; Weichao Mao; Jian Cao 001; Frederic Le Mouel; Minglu Li 001 (INFOCOM, 2019)

A fast and anti-matchability matching algorithm for content-based publish/subscribe systems. - Shiyou Qian; Jian Cao 001; Weichao Mao; Yanmin Zhu 006; Jiadi Yu; Minglu Li 001; Jie Wang 006 (Comput. Networks, 2019)

Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning. - Weichao Mao; Kaiqing Zhang; Erik Miehling; Tamer Basar (CDC, 2020)

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

Near-Optimal Regret Bounds for Model-Free RL in Non-Stationary Episodic MDPs. - Weichao Mao; Kaiqing Zhang; Ruihao Zhu; David Simchi-Levi; Tamer Basar (CoRR, 2020)

Semiparametric Information State Embedding for Policy Search under Imperfect Information. - Sujay Bhatt; Weichao Mao; Alec Koppel; Tamer Basar (CDC, 2021)

Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs. - Weichao Mao; Kaiqing Zhang; Ruihao Zhu; David Simchi-Levi; Tamer Basar (ICML, 2021)

Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration. - Weichao Mao; Tamer Basar; Lin F. Yang; Kaiqing Zhang (CoRR, 2021)

SIMPPO: a scalable and incremental online learning framework for serverless resource management. - Haoran Qiu; Weichao Mao; Archit Patke; Chen Wang 039; Hubertus Franke; Zbigniew T. Kalbarczyk; Tamer Basar; Ravishankar K. Iyer (SoCC, 2022)

Reinforcement learning for resource management in multi-tenant serverless platforms. - Haoran Qiu; Weichao Mao; Archit Patke; Chen Wang 039; Hubertus Franke; Zbigniew T. Kalbarczyk; Tamer Basar; Ravishankar K. Iyer (EuroMLSys@EuroSys, 2022)

On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning. - Weichao Mao; Lin Yang 011; Kaiqing Zhang; Tamer Basar (ICML, 2022)

A Mean-Field Game Approach to Cloud Resource Management with Function Approximation. - Weichao Mao; Haoran Qiu; Chen Wang 039; Hubertus Franke; Zbigniew Kalbarczyk; Ravishankar K. Iyer; Tamer Basar (NeurIPS, 2022)

Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity. - Weichao Mao; Haoran Qiu; Chen Wang 039; Hubertus Franke; Zbigniew Kalbarczyk; Ravishankar K. Iyer; Tamer Basar (NeurIPS, 2023)

AWARE: Automate Workload Autoscaling with Reinforcement Learning in Production Cloud Systems. - Haoran Qiu; Weichao Mao; Chen Wang 039; Hubertus Franke; Alaa Youssef; Zbigniew T. Kalbarczyk; Tamer Basar; Ravishankar K. Iyer (USENIX ATC, 2023)

Action Dynamics Task Graphs for Learning Plannable Representations of Procedural Tasks. - Weichao Mao; Ruta Desai; Michael Louis Iuzzolino; Nitin Kamra (CoRR, 2023)

Controlgym: Large-Scale Safety-Critical Control Environments for Benchmarking Reinforcement Learning Algorithms. - Xiangyuan Zhang; Weichao Mao; Saviz Mowlavi; Mouhacine Benosman; Tamer Basar (CoRR, 2023)

Provably Efficient Reinforcement Learning in Decentralized General-Sum Markov Games. - Weichao Mao; Tamer Basar (Dyn. Games Appl., 2023)

When Green Computing Meets Performance and Resilience SLOs. - Haoran Qiu; Weichao Mao; Chen Wang 039; Saurabh Jha; Hubertus Franke; Chandra Narayanaswami; Zbigniew Kalbarczyk; Tamer Basar; Ravishankar K. Iyer (DSN-S, 2024)

$ widetilde{O}(T^{-1})$ {C}onvergence to (coarse) correlated equilibria in full-information general-sum markov games. - Weichao Mao; Haoran Qiu; Chen Wang 039; Hubertus Franke; Zbigniew Kalbarczyk; Tamer Basar (L4DC, 2024)

Controlgym: Large-scale control environments for benchmarking reinforcement learning algorithms. - Xiangyuan Zhang; Weichao Mao; Saviz Mowlavi; Mouhacine Benosman; Tamer Basar (L4DC, 2024)

FLASH: Fast Model Adaptation in ML-Centric Cloud Platforms. - Haoran Qiu; Weichao Mao; Archit Patke; Shengkun Cui; Chen Wang 039; Hubertus Franke; Zbigniew Kalbarczyk; Tamer Basar; Ravi K. Iyer (MLSys, 2024)

Power-aware Deep Learning Model Serving with μ-Serve. - Haoran Qiu; Weichao Mao; Archit Patke; Shengkun Cui; Saurabh Jha; Chen Wang 039; Hubertus Franke; Zbigniew Kalbarczyk; Tamer Basar; Ravishankar K. Iyer (USENIX ATC, 2024)

Õ(T-1) Convergence to (Coarse) Correlated Equilibria in Full-Information General-Sum Markov Games. - Weichao Mao; Haoran Qiu; Chen Wang 039; Hubertus Franke; Zbigniew Kalbarczyk; Tamer Basar (CoRR, 2024)

Efficient Interactive LLM Serving with Proxy Model-based Sequence Length Prediction. - Haoran Qiu; Weichao Mao; Archit Patke; Shengkun Cui; Saurabh Jha; Chen Wang 039; Hubertus Franke; Zbigniew T. Kalbarczyk; Tamer Basar; Ravishankar K. Iyer (CoRR, 2024)

On Designing Market Model and Pricing Mechanisms for IoT Data Exchange. - Zhenzhe Zheng; Weichao Mao; Yidan Xing 001; Fan Wu 006 (IEEE Trans. Mob. Comput., 2024)

Decision Transformer as a Foundation Model for Partially Observable Continuous Control. - Xiangyuan Zhang; Weichao Mao; Haoran Qiu; Tamer Basar (ACC, 2025)

Model-Free Nonstationary Reinforcement Learning: Near-Optimal Regret and Applications in Multiagent Reinforcement Learning and Inventory Control. - Weichao Mao; Kaiqing Zhang; Ruihao Zhu; David Simchi-Levi; Tamer Basar (Manag. Sci., 2025)

Teaching Language Models to Critique via Reinforcement Learning. - Zhihui Xie 002; Jie Chen; Liyu Chen; Weichao Mao; Jingjing Xu; Lingpeng Kong (CoRR, 2025)