Subspace Optimization for Efficient Federated Learning under Heterogeneous Data
arXiv:2604.25467v1 Announce Type: new
Abstract: Federated learning increasingly operates in a large-model regime where communication, memory, and computation are all scarce. Typically, non-IID client data induce drift that degrades the stability and p…