Lower Bound for Randomized First Order Convex Optimization
Optimization and Control
2017-11-07 v2
Abstract
We provide an explicit construction and direct proof for the lower bound on the number of first order oracle accesses required for a randomized algorithm to minimize a convex Lipschitz function.
Keywords
Cite
@article{arxiv.1709.03594,
title = {Lower Bound for Randomized First Order Convex Optimization},
author = {Blake Woodworth and Nathan Srebro},
journal= {arXiv preprint arXiv:1709.03594},
year = {2017}
}
Comments
8 pages