no code implementations • 29 Nov 2021 • Dezhong Yao, Wanning Pan, Michael J O'Neill, Yutong Dai, Yao Wan, Hai Jin, Lichao Sun
To this end, this paper proposes FedHM, a novel heterogeneous federated model compression framework, distributing the heterogeneous low-rank models to clients and then aggregating them into a full-rank model.
no code implementations • 30 Jun 2021 • Dezhong Yao, Wanning Pan, Yutong Dai, Yao Wan, Xiaofeng Ding, Hai Jin, Zheng Xu, Lichao Sun
Federated learning enables multiple clients to collaboratively learn a global model by periodically aggregating the clients' models without transferring the local data.