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Sparsification of Binary CSPs

Abstract:
A cut ε-sparsifier of a weighted graph G is a re-weighted subgraph of G of (quasi)linear size that preserves the size of all cuts up to a multiplicative factor of ε. Since their introduction by Benczúr and Karger [STOC’96], cut sparsifiers have proved extremely influential and found various applications. Going beyond cut sparsifiers, Filtser and Krauthgamer [SIDMA’17] gave a precise classification of which binary Boolean CSPs are sparsifiable. In this paper, we extend their result to binary CSPs on arbitrary finite domains.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.4230/LIPIcs.STACS.2019.16

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
ORCID:
0000-0002-0263-159X


Publisher:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Host title:
36th International Symposium on Theoretical Aspects of Computer Science
Journal:
36th International Symposium on Theoretical Aspects of Computer Science More from this journal
Volume:
16
Pages:
16:1–16:8
Publication date:
2019-03-12
Acceptance date:
2018-12-20
Event location:
Berlin, Germany
DOI:
EISSN:
1868-8969


Pubs id:
pubs:955987
UUID:
uuid:da7375d5-ac8f-4806-a2ca-bd84580ee15e
Local pid:
pubs:955987
Source identifiers:
955987
Deposit date:
2019-01-03

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