The Dog Walking Theory: Rethinking Convergence in Federated Learning
The Dog Walking Theory: Rethinking Convergence in Federated Learning
Federated learning (FL) is a collaborative learning paradigm that allows different clients to train one powerful global model without sharing their private data. Although FL has demonstrated promising results in various applications, it is known to suffer from convergence issues caused by the data distribution shift across different clients, especially …