FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.

Paper list of federated learning: About system design

FedAnil+ is a novel lightweight, and secure Federated Deep Learning Model to address non-IID data, privacy concerns, and communication overhead. This repo hosts a simulation for FedAnil+ written in Python.

The communication efficiency of federated learning is improved by sparsifying the parameters uploaded by the clients.

Communication-Efficient Federated Learning via Transferring Codebooks

This project implements communication-efficient online federated learning strategies for resource-constrained devices using random Fourier features (RFFs) for kernel regression. It reduces communication overhead through partial-sharing and event-triggered updates, ensuring efficient local model updates.

This repository implements a communication-efficient online federated learning framework for nonlinear regression using partial sharing. Clients update local models with streaming data and share only portions of those updates with the server, reducing communication overhead while maintaining performance.

This work is a journal paper published at The Journal of Supercomputing in 2023, focusing on improving communication efficiency of a distributed learning system using age-based worker selection techniques.