A Reduction for Optimizing Lattice Submodular Functions with Diminishing Returns
Data Structures and Algorithms
2018-05-29 v2 Artificial Intelligence
Machine Learning
Abstract
A function is DR-submodular if it satisfies for all . Recently, the problem of maximizing a DR-submodular function subject to a budget constraint as well as additional constraints has received significant attention \cite{SKIK14,SY15,MYK15,SY16}. In this note, we give a generic reduction from the DR-submodular setting to the submodular setting. The running time of the reduction and the size of the resulting submodular instance depends only \emph{logarithmically} on . Using this reduction, one can translate the results for unconstrained and constrained submodular maximization to the DR-submodular setting for many types of constraints in a unified manner.
Keywords
Cite
@article{arxiv.1606.08362,
title = {A Reduction for Optimizing Lattice Submodular Functions with Diminishing Returns},
author = {Alina Ene and Huy L. Nguyen},
journal= {arXiv preprint arXiv:1606.08362},
year = {2018}
}