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Unbiased rounding of rational matrices

  • Max-Planck-Institut fur Informatik

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Résumé

Rounding a real-valued matrix to an integer one such that the rounding errors in all rows and columns are less than one is a classical problem. It has been applied to hypergraph coloring, in scheduling and in statistics. Here, it often is also desirable to round each entry randomly such that the probability of rounding it up equals its fractional part. This is known as unbiased rounding in statistics and as randomized rounding in computer science. We show how to compute such an unbiased rounding of an m × n matrix in expected time O(mnq2), where q is the common denominator of the matrix entries. We also show that if the denominator can be written as q = ∏i=1 qi for some integers qi, the expected runtime can be reduced to O(mn∑i=1 q2i). Our algorithm can be derandomised efficiently using the method of conditional probabilities. Our roundings have the additional property that the errors in all initial intervals of rows and columns are less than one.

langue originaleAnglais
titreFSTTCS 2006
Sous-titreFoundations of Software Technology and Theoretical Computer Science - 26th International Conference, Proceedings
rédacteurs en chef[initials] N. Arun-Kumar
EditeurSpringer Verlag
Pages200-211
Nombre de pages12
ISBN (imprimé)9783540499947
Les DOIs
étatPublié - 1 janv. 2006
Modification externeOui
Evénement26th International Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2006 - Kolkata, Inde
Durée: 13 déc. 200615 déc. 2006

Série de publications

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4337 LNCS
ISSN (imprimé)0302-9743
ISSN (Electronique)1611-3349

Une conférence

Une conférence26th International Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2006
Pays/TerritoireInde
La villeKolkata
période13/12/0615/12/06

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