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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, each of which have min-entropy n<sup>&#947;</sup> for an arbitrarily small constant &#947; &gt; 0. Our extractor is obtained by composing seeded extractors in simple ways. We(More)
  • Anup Rao
  • 2008
We give polynomial time computable extractors for \emph{low-weight affince sources}. A distribution is affine if it samples a random points from some unknown low dimensional subspace of $\mathbb{F}_2^n$. A distribution is low weight affine if the corresponding linear space has a basis of low-weight vectors. Low-weight affine sources are thus a(More)
We give polynomial-time, deterministic randomness extractors for sources generated in small space, where we model space s sources on (0,1)<sup>n</sup> as sources generated by width 2<sup>s</sup> branching programs: For every constant &#948;&gt;0, we can extract .99 &#948; n bits that are exponentially close to uniform (in variation distance) from space s(More)
In this paper, we present and analyze a simple and robust spectral algorithm for the stochastic block model with k blocks, for any k fixed. Our algorithm works with graphs having constant edge density, under an optimal condition on the gap between the density inside a block and the density between the blocks. As a co-product, we settle an open question(More)
We show how to efficiently simulate the sending of a single message M to a receiver who has partial information about the message, so that the expected number of bits communicated in the simulation is close to the amount of additional information that the message reveals to the receiver. This is a generalization and strengthening of the Slepian-Wolf(More)
The main result of this paper is an explicit disperser for two independent sources on n bits, each of entropy k=n<sup>o(1)</sup>. Put differently, setting N=2<sup>n</sup> and K=2<sup>k</sup>, we construct explicit N x N Boolean matrices for which no K x K submatrix is monochromatic. Viewed as adjacency matrices of bipartite graphs, this gives an explicit(More)
We show a connection between the semidefinite relaxation of unique games and their behavior under parallel repetition. Specifically,denoting by val(G) the value of a two-prover unique game G, andby sdpval(G) the value of a natural semidefinite program to approximate val(G), we prove that for every l epsi N, if sdpval(G) ges 1-delta, then val(G<sup>l</sup>)(More)