Approximation-friendly discrepancy rounding

N. Bansal, V. Nagarajan

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

10 Citations (Scopus)
1 Downloads (Pure)

Abstract

Rounding linear programs using techniques from discrepancy is a recent approach that has been very successful in certain settings. However this method also has some limitations when compared to approaches such as randomized and iterative rounding. We provide an extension of the discrepancy-based rounding algorithm due to Lovett-Meka that (i) combines the advantages of both randomized and iterated rounding, (ii) makes it applicable to settings with more general combinatorial structure such as matroids. As applications of this approach, we obtain new results for various classical problems such as linear system rounding, degree-bounded matroid basis and low congestion routing.
Original languageEnglish
Title of host publicationInteger Programming and Combinatorial Optimization
Subtitle of host publication18th International Conference, IPCO 2016, Liège, Belgium, June 1-3, 2016, Proceedings
EditorsQ. Louveaux, M. Skutella
Place of PublicationDordrecht
PublisherSpringer
Pages375-386
ISBN (Electronic)978-3-319-33460-8
ISBN (Print)978-3-319-33461-5
DOIs
Publication statusPublished - 2016

Publication series

NameLecture Notes in Computer Science
Volume9682

Fingerprint

Dive into the research topics of 'Approximation-friendly discrepancy rounding'. Together they form a unique fingerprint.

Cite this