Yizhi Zhou

Exploring Amplified Heterogeneity Arising From Heavy-Tailed Distributions in Federated Learning

2024 · IEEE Transactions on Mobile Computing

Federated Learning (FL) has emerged as a privacy-preserving paradigm enabling collaborative model training among distributed clients. However, current FL methods operate under the closed-world assumption, i.e., all local training data originates from a global labeled …