Papers. [Google Scholar]

* denotes equal contribution or alphabetical order

Conferences/Journals/Preprints

PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms

Wenjie Li^*, Haoze Li^*, Qifan Song, Jean Honorio
In Preparation, codebase arXiv:2303.04030

Federated X-Armed Bandit

Wenjie Li, Qifan Song, Jean Honorio, Guang Lin.
In Submission to ICML. arXiv:2205.15268.

On the Sharp Analysis of Online Blackbox Optimization

Wenjie Li, Jean Honorio, Qifan Song
Under Revision.

Federated Online Sparse Decision Making

Chi-Hua Wang, Wenjie Li, Guang Lin.
In Submission to TMLR. arXiv: 2202.13448.

Always-Valid Risk Bounds for Low-Rank Online Matrix Completion

Chi-Hua Wang^*, Wenjie Li^*.
In Submission to JMLR. arXiv: 2211.10363.

Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization

Wenjie Li^*, Chi-Hua Wang^*, Guang Cheng, Qifan Song.
In Submission to TMLR. arXiv: 2106.09215.

A Simple Unified Framework for High Dimensional Bandit Problems

Wenjie Li, Adarsh Barik, Jean Honorio.
[ICML’22]. Proceedings of the 39th International Conference on Machine Learning, 2022.

Variance Reduction on General Adaptive Stochastic Mirror Descent

Wenjie Li, Zhanyu Wang, Yichen Zhang, Guang Cheng.
[MLJ’22]. Machine Learning. 2022

AdaX: Adaptive Gradient Descent with Exponential Long Term Memory

Wenjie Li, Zhaoyang Zhang, Xinjiang Wang, Ping Luo.
Technical Report. arXiv: 2004.09740.

Workshops

Optimum-statistical Collaboration Towards Efficient Black-box Optimization

Wenjie Li^*, Chi-Hua Wang^*, Guang Cheng.
[NeurIPS-OPT’21]. NeurIPS Optimization for Machine Learning Workshop 2021.

Variance Reduction on Adaptive Stochastic Mirror Descent

Wenjie Li, Zhanyu Wang, Yichen Zhang, Guang Cheng.
[NeurIPS-OPT’20]. NeurIPS Optimization for Machine Learning Workshop 2020. (Spotlight)