Fast algorithms for maximizing monotone nonsubmodular functions

In recent years, with the more and more researchers studying the problem of maximizing monotone (nonsubmodular) objective functions, the approximation algorithms for this problem have gotten much progress by using some interesting techniques. In this paper, we develop the approximation algorithms fo...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Journal of combinatorial optimization Ročník 43; číslo 5; s. 1655 - 1670
Hlavní autori: Liu, Bin, Hu, Miaomiao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.07.2022
Springer Nature B.V
Predmet:
ISSN:1382-6905, 1573-2886
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In recent years, with the more and more researchers studying the problem of maximizing monotone (nonsubmodular) objective functions, the approximation algorithms for this problem have gotten much progress by using some interesting techniques. In this paper, we develop the approximation algorithms for maximizing a monotone function f with generic submodularity ratio γ subject to certain constraints. Our first result is a simple algorithm that gives a ( 1 - e - γ - ϵ ) -approximation for a cardinality constraint using O ( n ϵ l o g n ϵ ) queries to the function value oracle. The second result is a new variant of the continuous greedy algorithm for a matroid constraint. We combine the variant of continuous greedy method with the contention resolution schemes to find a solution with approximation ratio ( γ 2 ( 1 - 1 e ) 2 - O ( ϵ ) ) , and the algorithm makes O ( r n ϵ - 4 l o g 2 n ϵ ) queries to the function value oracle.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1382-6905
1573-2886
DOI:10.1007/s10878-021-00717-1