Tianying Lu

Generalizable Heterogeneity-aware Federated Feature and Basic-matrix Consistency Learning

As an emerging distributed learning paradigm, Federated Learning (FL) facilitates collaborative training among multiple clients without sharing raw data. However, the classic FL still faces significant challenges due to feature/model heterogeneity and catastrophic forgetting, which seriously hinder