# Asynchronous decentralized accelerated stochastic gradient descent

**Authors:** Guanghui Lan, Yi Zhou  
**arXiv:** [1809.09258](https://arxiv.org/abs/1809.09258)  
**Date:** 2018-09-24  
**Summary page:** https://www.summarizepaper.com/fr/paper/1809.09258v1/

## Abstract

In this work, we introduce an asynchronous decentralized accelerated stochastic gradient descent type of method for decentralized stochastic optimization, considering communication and synchronization are the major bottlenecks. We establish $\mathcal{O}(1/\epsilon)$ (resp., $\mathcal{O}(1/\sqrt{\epsilon})$) communication complexity and $\mathcal{O}(1/\epsilon^2)$ (resp., $\mathcal{O}(1/\epsilon)$) sampling complexity for solving general convex (resp., strongly convex) problems.