# Distributed SAGA: Maintaining linear convergence rate with limited communication

arXiv: https://arxiv.org/abs/1705.10405 · HTML: https://mlsanity.com/paper/1705.10405/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 May 2017.

## Built on by (most cited first, 1 of 1)

- [Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology](https://mlsanity.com/paper/2207.03730/) (2022)

## Abstract (arXiv)

In recent years, variance-reducing stochastic methods have shown great practical performance, exhibiting linear convergence rate when other stochastic methods offered a sub-linear rate. However, as datasets grow ever bigger and clusters become widespread, the need for fast distribution methods is pressing. We propose here a distribution scheme for SAGA which maintains a linear convergence rate, even when communication between nodes is limited.