mailitics

Tag: fl

  • Generalization in Federated Learning: A Conditional Mutual Information Framework

    Generalization in Federated Learning: A Conditional Mutual Information Framework arXiv:2503.04091v1 Announce Type: new Abstract: Federated Learning (FL) is a widely adopted privacy-preserving distributed learning framework, yet its generalization performance remains less explored compared to centralized learning. In FL, the generalization error consists of two components: the out-of-sample gap, which measures the gap between the empirical…

  • A Survey on Cluster-based Federated Learning

    A Survey on Cluster-based Federated Learning arXiv:2501.17512v1 Announce Type: new Abstract: As the industrial and commercial use of Federated Learning (FL) has expanded, so has the need for optimized algorithms. In settings were FL clients’ data is non-independently and identically distributed (non-IID) and with highly heterogeneous distributions, the baseline FL approach seems to fall short.…