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Author Doerr, Benjamin ♦ Wahlstrm, Magnus
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Subject Keyword Randomized rounding ♦ Algorithm engineering ♦ Approximation algorithms
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.
ISSN 10846654
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-01-07
Publisher Place New York
e-ISSN 10846654
Journal Journal of Experimental Algorithmics (JEA)
Volume Number 19
Page Count 18
Starting Page 1.1
Ending Page 1.18


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Source: ACM Digital Library