@inproceedings{69e513f19d0e4e86b15ee3d28e66142d,
title = "Unbiased rounding of rational matrices",
abstract = "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 = ∏ℓi=1 qi for some integers qi, the expected runtime can be reduced to O(mn∑ℓi=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.",
author = "Benjamin Doerr and Christian Klein",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.; 26th International Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2006 ; Conference date: 13-12-2006 Through 15-12-2006",
year = "2006",
month = jan,
day = "1",
doi = "10.1007/11944836\_20",
language = "English",
isbn = "9783540499947",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "200--211",
editor = "Arun-Kumar, \{[initials] N.\}",
booktitle = "FSTTCS 2006",
}