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.

Federated Optimization in Heterogeneous Networks (MLSys '20)

Fair Resource Allocation in Federated Learning (ICLR '20)

FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.

Symbolic Continuous-Time Gaussian Belief Propagation Framework with Ceres Interoperability

Distributed Linear Programming Solver on top of Apache Spark

DISROPT: A Python framework for distributed optimization

This library is an implementation of the algorithm described in Distributed Trajectory Estimation with Privacy and Communication Constraints: a Two-Stage Distributed Gauss-Seidel Approach.

Implementation of (overlap) local SGD in Pytorch

A package for solving optimal power flow problems using distributed algorithms.

FedDANE: A Federated Newton-Type Method (Asilomar Conference on Signals, Systems, and Computers ‘19)

Communication-efficient decentralized SGD (Pytorch)

Scalable, structured, dynamically-scheduled hyperparameter optimization.

A ray-based library of Distributed POPulation-based OPtimization for Large-Scale Black-Box Optimization.

MATLAB implementation of the paper "Distributed Optimization of Average Consensus Containment with Multiple Stationary Leaders" [arXiv 2022].

Sparse Convex Optimization Toolkit (SCOT)

tvopt is a prototyping and benchmarking Python framework for time-varying (or online) optimization.

MATLAB implementation of the paper "Online Distributed Optimal Power Flow with Equality Constraints" [arXiv 2022].

Implementation of Redundancy Infused SGD for faster distributed SGD.