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...
Sources of training data suitable for language modeling of conversational speech are limited. In this paper, we show how training data can be supplemented with text from the web ï...
Various efforts ([?, ?, ?]) have been made in recent years to derandomize probabilistic algorithms using the complexity theoretic assumption that there exists a problem in E = dti...
Russell Impagliazzo, Ronen Shaltiel, Avi Wigderson
We consider the problem of randomness extraction from independent sources. We construct an extractor that can extract from a constant number of independent sources of length n, ea...
Nowadays the concept of trust in computer communications starts to get more and more popular. While the idea of trust in human interaction seems to be obvious and understandable i...