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cs.LG2022
Bayesian Federated Neural Matching that Completes Full Information
Peng Xiao, Samuel Cheng
Federated learning is a contemporary machine learning paradigm where locally trained models are distilled into a global model. Due to the intrinsic permutation invariance of neural…
cs.LG2022
Investigating Neuron Disturbing in Fusing Heterogeneous Neural Networks
Biao Zhang, Shuqin Zhang
Fusing deep learning models trained on separately located clients into a global model in a one-shot communication round is a straightforward implementation of Federated Learning. A…