14 citations · 50 across the 18 of their papers we have counts for
4 papers · 1 filter
Federated Short-Term Load Forecasting with Personalization Layers for Heterogeneous Clients
Shourya Bose, Kibaek Kim
The advent of smart meters has enabled pervasive collection of energy consumption data for training short-term load forecasting (STLF) models. In response to privacy concerns, fede…
APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning
Minseok Ryu, Youngdae Kim, Kibaek Kim +1
Federated learning (FL) enables training models at different sites and updating the weights from the training instead of transferring data to a central location and training as in…
Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates
Minseok Ryu, Kibaek Kim
Differential privacy (DP) techniques can be applied to the federated learning model to statistically guarantee data privacy against inference attacks to communication among the lea…
Differentially Private Federated Learning via Inexact ADMM
Minseok Ryu, Kibaek Kim
Differential privacy (DP) techniques can be applied to the federated learning model to protect data privacy against inference attacks to communication among the learning agents. Th…