6 citations · 7 across the 4 of their papers we have counts for
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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…
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…
Probabilistic Federated Learning of Neural Networks Incorporated with Global Posterior Information
Peng Xiao, Samuel Cheng
In federated learning, models trained on local clients are distilled into a global model. Due to the permutation invariance arises in neural networks, it is necessary to match the…
Neural Network for NILM Based on Operational State Change Classification
Peng Xiao, Samuel Cheng
Energy disaggregation in a non-intrusive way estimates appliance level electricity consumption from a single meter that measures the whole house electricity demand. Recently, with…