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)