@inproceedings{09197dc1e8f6484596f9436987f5ac69,
title = "Unconstrained submodular maximization with constant adaptive complexity",
abstract = "In this paper, we consider the unconstrained submodular maximization problem. We propose the first algorithm for this problem that achieves a tight (1/2 − ε)-approximation guarantee using {\~O}(ε−1) adaptive rounds and a linear number of function evaluations. No previously known algorithm for this problem achieves an approximation ratio better than 1/3 using less than Ω(n) rounds of adaptivity, where n is the size of the ground set. Moreover, our algorithm easily extends to the maximization of a non-negative continuous DR-submodular function subject to a box constraint, and achieves a tight (1/2 − ε)-approximation guarantee for this problem while keeping the same adaptive and query complexities.",
keywords = "Low adaptive complexity, Parallel computation, Submodular maximization",
author = "Lin Chen and Moran Feldman and Amin Karbasi",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.; 51st Annual ACM SIGACT Symposium on Theory of Computing, STOC 2019 ; Conference date: 23-06-2019 Through 26-06-2019",
year = "2019",
month = jun,
day = "23",
doi = "10.1145/3313276.3316327",
language = "American English",
series = "Proceedings of the Annual ACM Symposium on Theory of Computing",
publisher = "Association for Computing Machinery",
pages = "102--113",
editor = "Moses Charikar and Edith Cohen",
booktitle = "STOC 2019 - Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing",
address = "United States",
}