247 search results - page 2 / 50» Extracting All the Randomness from a Weakly Random Source |

COCO

2009

Springer

14 years 3 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

14 years 3 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

14 years 25 days 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 5 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

14 years 3 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...