A Refined Analysis of Submodular Greedy
Data Structures and Algorithms
2021-03-16 v2
Abstract
Many algorithms for maximizing a monotone submodular function subject to a knapsack constraint rely on the natural greedy heuristic. We present a novel refined analysis of this greedy heuristic which enables us to: reduce the enumeration in the tight -approximation of [Sviridenko 04] from subsets of size three to two; present an improved upper bound of for the classic algorithm which returns the better between a single element and the output of the greedy heuristic.
Cite
@article{arxiv.2102.12879,
title = {A Refined Analysis of Submodular Greedy},
author = {Ariel Kulik and Roy Schwartz and Hadas Shachnai},
journal= {arXiv preprint arXiv:2102.12879},
year = {2021}
}