247 search results - page 2 / 50 » Extracting All the Randomness from a Weakly Random Source |
COCO
2009
Springer
13 years 11 months ago
2009
Springer
—A simple averaging argument shows that given a randomized algorithm A and a function f such that for every input x, Pr[A(x) = f(x)] ≥ 1−ρ (where the probability is over the...
SIGIR
2009
ACM
13 years 11 months ago
2009
ACM
When search is against structured documents, it is beneficial to extract information from user queries in a format that is consistent with the backend data structure. As one step...
COCO
2006
Springer
13 years 8 months ago
2006
Springer
Let C be a class of distributions over {0, 1}n . A deterministic randomness extractor for C is a function E : {0, 1}n {0, 1}m such that for any X in C the distribution E(X) is sta...
CORR
2010
Springer
13 years 1 months ago
2010
Springer
Suppose Alice and Bob receive strings of unbiased independent but noisy bits from some random source. They wish to use their respective strings to extract a common sequence of ran...
FSTTCS
2009
Springer
13 years 11 months ago
2009
Springer
Randomness extractors are efficient algorithms which convert weak random sources into nearly perfect ones. While such purification of randomness was the original motivation for c...