Xuchuang Wang

I am a postdoc at University of Massachusetts - Amherst, working with Don Towsley and Mohammad Hajiesmaili. I received my Ph.D. in the Department of Computer Science & Engineering at The Chinese University of Hong Kong under the guidance of John C.S. Lui.

My research is dedicated to designing algorithms for sequential decision-making under uncertainty, with a particular focus on online learning algorithms incorporating multi-armed bandit feedback and distributed multi-agent cooperation.

selected publications

NeurIPS

Multi-Fidelity Multi-Armed Bandits Revisited

Xuchuang Wang, Qingyun Wu , Wei Chen , and John C.S. Lui

In Advances in Neural Information Processing Systems , 2023

Bib PDF Slides

@inproceedings{wang2023fidelity,
  title = {Multi-Fidelity Multi-Armed Bandits Revisited},
  author = {Wang, Xuchuang and Wu, Qingyun and Chen, Wei and Lui, John C.S.},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2023}
}

ICLR

Achieve Near-Optimal Individual Regret & Low Communications in Multi-Agent Bandits

Xuchuang Wang, Lin Yang , Yu-zhen Janice Chen , Xutong Liu , Mohammad Hajiesmaili , Don Towsley , and John C.S. Lui

In International Conference on Learning Representations , 2023

Bib PDF Slides

@inproceedings{wang2023achieve,
  title = {Achieve Near-Optimal Individual Regret \&amp; Low Communications in Multi-Agent Bandits},
  author = {Wang, Xuchuang and Yang, Lin and Chen, Yu-zhen Janice and Liu, Xutong and Hajiesmaili, Mohammad and Towsley, Don and Lui, John C.S.},
  booktitle = {International Conference on Learning Representations},
  year = {2023},
}

ICML

Multiple-Play Stochastic Bandits with Shareable Finite-Capacity Arms

Xuchuang Wang, Hong Xie , and John C.S. Lui

In Proceedings of the 39th International Conference on Machine Learning , 2022

Bib PDF Slides

@inproceedings{wang2022multiple,
  title = {Multiple-Play Stochastic Bandits with Shareable Finite-Capacity Arms},
  author = {Wang, Xuchuang and Xie, Hong and Lui, John C.S.},
  booktitle = {Proceedings of the 39th International Conference on Machine Learning},
  pages = {23181--23212},
  year = {2022},
  organization = {PMLR},
}