1 citations · 1 across the 4 of their papers we have counts for
4 papers
DaringFed: A Dynamic Bayesian Persuasion Pricing for Online Federated Learning under Two-sided Incomplete Information
Yun Xin, Jianfeng Lu, Shuqin Cao +3
Online Federated Learning (OFL) is a real-time learning paradigm that sequentially executes parameter aggregation immediately for each random arriving client. To motivate clients t…
LEAP: Optimization Hierarchical Federated Learning on Non-IID Data with Coalition Formation Game
Jianfeng Lu, Yue Chen, Shuqin Cao +3
Although Hierarchical Federated Learning (HFL) utilizes edge servers (ESs) to alleviate communication burdens, its model performance will be degraded by non-IID data and limited co…
Rating Protocol Design for Extortion and Cooperation in the Crowdsourcing Contest Dilemma
Jianfeng Lu, Yun Xin, Zhao Zhang +3
Crowdsourcing has emerged as a paradigm for leveraging human intelligence and activity to solve a wide range of tasks. However, strategic workers will find enticement in their self…
Game-Theoretic Design of Optimal Two-Sided Rating Protocols for Service Exchange Dilemma in Crowdsourcing
Jianfeng Lu, Yun Xin, Zhao Zhang +2
Despite the increasing popularity and successful examples of crowdsourcing, it is stripped of aureole when collective efforts are derailed or severely hindered by elaborate sabotag…