Cross-silo Federated Learning playground in Python. Discover 7 real-world federated datasets to test your new FL strategies and try to beat the leaderboard.

🎡 Build Python wheels for all the platforms with minimal configuration.

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs o…

LaTeX template in accordance with the University of Southern California Theses and Dissertations Formatting Guidelines.

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models. ICML 2021

This repository is an official Tensorflow 2 implementation of Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Code for "Federated Accelerated Stochastic Gradient Descent" (NeurIPS 2020)

Experiments code for the paper "Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques"

A curated and opinionated list of resources for Chief Technology Officers, with the emphasis on startups

Neural Architecture Search (NAS) papers with code

FedNLP: An Industry and Research Integrated Platform for Federated Learning in Natural Language Processing, Backed by FedML, Inc. The Previous Research Version is Accepted to NAACL 2022

Official code for "Throughput-Optimal Topology Design for Cross-Silo Federated Learning" (NeurIPS'20)

PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.

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

Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder and reinforcement learning. ICML 2019

🧠🗼

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Federated learning experiment using TensorFlow.js

open OTA service for the Connected Cars

Mass Service Engine in Cluster(MSEC) is opened source by QQ team from Tencent. It is a backend DEV &OPS engine, including RPC,name finding,load balance,monitoring,release and capacity management.