8 citations · 11 across the 5 of their papers we have counts for
5 papers
(Private) Kernelized Bandits with Distributed Biased Feedback
Fengjiao Li, Xingyu Zhou, Bo Ji
In this paper, we study kernelized bandits with distributed biased feedback. This problem is motivated by several real-world applications (such as dynamic pricing, cellular network…
Differentially Private Linear Bandits with Partial Distributed Feedback
Fengjiao Li, Xingyu Zhou, Bo Ji
In this paper, we study the problem of global reward maximization with only partial distributed feedback. This problem is motivated by several real-world applications (e.g., cellul…
Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach
Fengjiao Li, Jia Liu, Bo Ji
In this paper, we study the problem of fair worker selection in Federated Learning systems, where fairness serves as an incentive mechanism that encourages more workers to particip…
Waiting but not Aging: Optimizing Information Freshness Under the Pull Model
Fengjiao Li, Yu Sang, Zhongdong Liu +3
The Age-of-Information is an important metric for investigating the timeliness performance in information-update systems. In this paper, we study the AoI minimization problem under…
Combinatorial Sleeping Bandits with Fairness Constraints
Fengjiao Li, Jia Liu, Bo Ji
The multi-armed bandit (MAB) model has been widely adopted for studying many practical optimization problems (network resource allocation, ad placement, crowdsourcing, etc.) with u…