A fast double greedy algorithm for non-monotone DR-submodular function maximization Academic Article

abstract

• We study the problem of maximizing non-monotone diminish return (DR)-submodular function on the bounded integer lattice, which is a generalization of submodular set function. DR-submodular functions consider the case that we can choose multiple copies for each element in the ground set. This generalization has many applications in machine learning. In this paper, we propose a [Formula: see text]-approximation algorithm with a running time of [Formula: see text], where [Formula: see text] is the size of the ground set, [Formula: see text] is the upper bound of integer lattice. Discovering important properties of DR-submodular function, we propose a fast double greedy algorithm which improves the running time.

authors

• Gu, Shuyang

published proceedings

• DISCRETE MATHEMATICS ALGORITHMS AND APPLICATIONS

author list (cited authors)

• Gu, S., Shi, G., Wu, W., & Lu, C.

citation count

• 7

complete list of authors

• Gu, Shuyang||Shi, Ganquan||Wu, Weili||Lu, Changhong

publication date

• February 2020

publisher

• World Scientific Publishing  Publisher

keywords

• Bounded Integer Lattice
• Double Greedy
• Dr-submodular
• Unconstrained Submodular Maximization

Digital Object Identifier (DOI)

• 10.1142/S179383092050007X

start page

• 2050007

end page

• 2050007

volume

• 12

issue

• 1

URL

• http://dx.doi.org/10.1142/s179383092050007x