Weichao Mao

Orcid: 0000-0001-8301-4173

According to our database1, Weichao Mao authored at least 22 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Õ(T<sup>-1</sup>) Convergence to (Coarse) Correlated Equilibria in Full-Information General-Sum Markov Games.
CoRR, 2024

2023
Provably Efficient Reinforcement Learning in Decentralized General-Sum Markov Games.
Dyn. Games Appl., March, 2023

Controlgym: Large-Scale Safety-Critical Control Environments for Benchmarking Reinforcement Learning Algorithms.
CoRR, 2023

Action Dynamics Task Graphs for Learning Plannable Representations of Procedural Tasks.
CoRR, 2023

AWARE: Automate Workload Autoscaling with Reinforcement Learning in Production Cloud Systems.
Proceedings of the 2023 USENIX Annual Technical Conference, 2023

Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
A Mean-Field Game Approach to Cloud Resource Management with Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

Reinforcement learning for resource management in multi-tenant serverless platforms.
Proceedings of the EuroMLSys '22: Proceedings of the 2nd European Workshop on Machine Learning and Systems, Rennes, France, April 5, 2022

SIMPPO: a scalable and incremental online learning framework for serverless resource management.
Proceedings of the 13th Symposium on Cloud Computing, SoCC 2022, 2022

2021
Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration.
CoRR, 2021

Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs.
Proceedings of the 38th International Conference on Machine Learning, 2021

Semiparametric Information State Embedding for Policy Search under Imperfect Information.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020
Near-Optimal Regret Bounds for Model-Free RL in Non-Stationary Episodic MDPs.
CoRR, 2020

POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019
A fast and anti-matchability matching algorithm for content-based publish/subscribe systems.
Comput. Networks, 2019

Adjusting Matching Algorithm to Adapt to Workload Fluctuations in Content-based Publish/Subscribe Systems.
Proceedings of the 2019 IEEE Conference on Computer Communications, 2019

Pricing for Revenue Maximization in IoT Data Markets: An Information Design Perspective.
Proceedings of the 2019 IEEE Conference on Computer Communications, 2019

Challenges and Opportunities in IoT Data Markets.
Proceedings of the Fourth International Workshop on Social Sensing, 2019

2018
Adjusting Matching Algorithm to Adapt to Dynamic Subscriptions in Content-Based Publish/Subscribe Systems.
Proceedings of the IEEE International Conference on Parallel & Distributed Processing with Applications, 2018

Online Pricing for Revenue Maximization with Unknown Time Discounting Valuations.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018


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