Fair Resource Allocation in Federated Learning

ICLR 2020 Tian LiMaziar SanjabiAhmad BeiramiVirginia Smith

Federated learning involves training statistical models in massive, heterogeneous networks. Naively minimizing an aggregate loss function in such a network may disproportionately advantage or disadvantage some of the devices... (read more)

PDF Abstract ICLR 2020 PDF ICLR 2020 Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet