Yue Wang

Orcid: 0009-0001-9786-052X

Affiliations:
  • University of Central Florida, Orlando, FL, USA
  • University at Buffalo, the State University of New York, NY, USA (Ph.D., 2023)


According to our database1, Yue Wang authored at least 13 papers between 2020 and 2023.

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

Timeline

Legend:

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Links

Online presence:

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Bibliography

2023
Distributionally Robust Optimization Efficiently Solves Offline Reinforcement Learning.
CoRR, 2023

A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems.
IROS, 2023

Model-Free Robust Average-Reward Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Robust Average-Reward Markov Decision Processes.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
A Robust and Constrained Multi-Agent Reinforcement Learning Framework for Electric Vehicle AMoD Systems.
CoRR, 2022

Robust Constrained Reinforcement Learning.
CoRR, 2022

Finite-Time Error Bounds for Greedy-GQ.
CoRR, 2022

Data-Driven Robust Multi-Agent Reinforcement Learning.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Policy Gradient Method For Robust Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

2021
Finite-Sample Analysis for Two Time-scale Non-linear TDC with General Smooth Function Approximation.
CoRR, 2021

Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Online Robust Reinforcement Learning with Model Uncertainty.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020


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