Nov 8, 2021 · In this paper, we consider a two-level incentive mechanism design problem. In the lower level, the data owners are allowed to support the FL training tasks of ...

Abstract—Federated Learning (FL) is a privacy-preserving collaborative learning approach that trains artificial intelligence.

Federated Learning (FL) is a privacy-preserving collaborative learning approach that trains artificial intelligence (AI) models without revealing local ...

Nov 7, 2024 · In this paper, by considering the interactions among the TP, LMOs and workers, we propose a three-layer hierarchical game framework.

In this paper, by considering the interactions among the TP, LMOs and workers, we propose a three-layer hierarchical game framework.

Jul 4, 2024 · Ng et al., “A hierarchical incentive design toward motivating participation in coded federated learning,” IEEE J. Sel. Areas Commun., vol ...

Hierarchical federated learning (HFL) can effectively alleviate the communication bottleneck of traditional federated learning.

Leung, and D. I. Kim, “A hierarchical. 420 incentive design toward motivating participation in coded federated learning,” IEEE Journal on. 421. Selected Areas ...

A novel framework to address straggling and privacy issues for federated learning (FL)-based mobile application services, taking into account limited ...

Ng, A hierarchical incentive design toward motivating participation in coded federated learning, IEEE Journal on Selected Areas in Communications, № 40, с.