24 citations · 37 across the 8 of their papers we have counts for
6 papers · 1 filter
PyXAB -- A Python Library for -Armed Bandit and Online Blackbox Optimization Algorithms
Wenjie Li, Haoze Li, Jean Honorio +1
We introduce a Python open-source library for -armed bandit and online blackbox optimization named PyXAB. PyXAB contains the implementations for more than 10 $\mathcal…
Always Valid Risk Monitoring for Online Matrix Completion
Chi-Hua Wang, Wenjie Li
Always-valid concentration inequalities are increasingly used as performance measures for online statistical learning, notably in the learning of generative models and supervised l…
Federated X-Armed Bandit
Wenjie Li, Qifan Song, Jean Honorio +1
This work establishes the first framework of federated -armed bandit, where different clients face heterogeneous local objective functions defined on the same domain a…
Federated Online Sparse Decision Making
Chi-Hua Wang, Wenjie Li, Guang Cheng +1
This paper presents a novel federated linear contextual bandits model, where individual clients face different K-armed stochastic bandits with high-dimensional decision context and…
Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization
Wenjie Li, Chi-Hua Wang, Guang Cheng +1
In this paper, we make the key delineation on the roles of resolution and statistical uncertainty in hierarchical bandits-based black-box optimization algorithms, guiding a more ge…
Variance Reduction on General Adaptive Stochastic Mirror Descent
Wenjie Li, Zhanyu Wang, Yichen Zhang +1
In this work, we investigate the idea of variance reduction by studying its properties with general adaptive mirror descent algorithms in nonsmooth nonconvex finite-sum optimizatio…