A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization
[article]
2019
arXiv
pre-print
Under appropriate cooperation protocols and parameter choices, fully decentralized solutions for stochastic optimization have been shown to match the performance of centralized solutions and result in linear speedup (in the number of agents) relative to non-cooperative approaches in the strongly-convex setting. More recently, these results have been extended to the pursuit of first-order stationary points in non-convex environments. In this work, we examine in detail the dependence of
arXiv:1910.13852v1
fatcat:ohvqqkggoneltf4kebtq5qex5q