NDLI: Randomized Rounding in the Presence of a Cardinality Constraint

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Randomized Rounding in the Presence of a Cardinality Constraint

Content Provider	ACM Digital Library
Author	Doerr, Benjamin Wahlstrm, Magnus
Copyright Year	2014
Abstract	We consider the problem of generating randomized roundings that satisfy a single cardinality constraint and admit Chernoff-type large deviation bounds for weighted sums of the variables. That this can be done efficiently was proven by Srinivasan [2001], a different approach was later given by the first author [Doerr 2006]. In this work, we (a) present an improved version of the bitwise derandomization given by Doerr, (b) give the first derandomization of Srinivasan's tree-based randomized approach and prove its correctness, and (c) experimentally compare the resulting algorithms. Our experiments show that adding a single cardinality constraint typically reduces the rounding errors and only moderately increases the running times. In general, our derandomization of the tree-based approach is superior to the derandomized bitwise one, while the two randomized versions produce very similar rounding errors. When implementing the derandomized tree-based approach, however, the choice of the tree is important.
Starting Page	1.1
Ending Page	1.18
Page Count	18
File Format	PDF
ISSN	10846654
e-ISSN	10846654
DOI	10.1145/2594409
Journal	Journal of Experimental Algorithmics (JEA)
Volume Number	19
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-01-07
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Randomized rounding Algorithm engineering Approximation algorithms
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science

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