Abstract: Federated Learning (FL) is a distributed machine learning method that ensures the privacy and security of participants’ data by avoiding direct data upload to a central node for training.

This repository is PyTorch implementation for paper CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization which is ...

Abstract: Split Federated Learning (SFL) improves scalability of Split Learning (SL) by enabling parallel computing of the learning tasks on multiple clients. However, state-of-the-art SFL schemes ...

Welcome to the Zero to Mastery Learn PyTorch for Deep Learning course, the second best place to learn PyTorch on the internet (the first being the PyTorch documentation). 00 - PyTorch Fundamentals ...