FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants
Federated learning (FL) provides a privacy-preserving approach for collaborative training of machine learning models. Given the potential data heterogeneity, it is crucial to select appropriate collaborators for each FL participant (FL-PT) based on data complementarity. Recent studies have addressed this challenge. Similarly, it is imperative to consider the inter-individual relationships …