FedLab: A Flexible Federated Learning Framework

07/24/2021
by   Dun Zeng, et al.
0

Federated learning (FL) is a machine learning field in which researchers try to facilitate model learning process among multiparty without violating privacy protection regulations. Considerable effort has been invested in FL optimization and communication related researches. In this work, we introduce FedLab, a lightweight open-source framework for FL simulation. The design of FedLab focuses on FL algorithm effectiveness and communication efficiency. Also, FedLab is scalable in different deployment scenario. We hope FedLab could provide flexible API as well as reliable baseline implementations, and relieve the burden of implementing novel approaches for researchers in FL community.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/09/2023

An Empirical Study of Bugs in Open-Source Federated Learning Framework

Federated learning (FL), as a decentralized machine learning solution to...
research
12/16/2020

More Industry-friendly: Federated Learning with High Efficient Design

Although many achievements have been made since Google threw out the par...
research
01/21/2022

FedComm: Federated Learning as a Medium for Covert Communication

Proposed as a solution to mitigate the privacy implications related to t...
research
02/15/2023

Experimenting with Emerging ARM and RISC-V Systems for Decentralised Machine Learning

Decentralised Machine Learning (DML) enables collaborative machine learn...
research
10/24/2022

NVIDIA FLARE: Federated Learning from Simulation to Real-World

Federated learning (FL) enables the building of robust and generalizable...
research
07/15/2022

Introducing Federated Learning into Internet of Things ecosystems – preliminary considerations

Federated learning (FL) was proposed to facilitate the training of model...
research
05/17/2021

EasyFL: A Low-code Federated Learning Platform For Dummies

Academia and industry have developed several platforms to support the po...

Please sign up or login with your details

Forgot password? Click here to reset