# Federated-Learning

**Repository Path**: wardseptember/Federated-Learning

## Basic Information

- **Project Name**: Federated-Learning
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-07-16
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Federated-Learning

We implement the paper [Communication-Efficient Learning of Deep Networks from Decentralized Data](https://arxiv.org/abs/1602.05629). Its blog is [here](https://research.googleblog.com/2017/04/federated-learning-collaborative.html).

We wish to explore several possible approaches:
1. server pulling gradient update from clients;
2. clients eagerly train and push updates to server;
3. extend to multi-server; servers gossip to sync;
4. client-only p2p gradient updates