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- Anup Rao
- SIAM J. Comput.
- 2008

In a two player game, a referee asks two cooperating players (who are not allowed to communicate) questions sampled from some distribution and decides whether they win or not based on some predicate of the questions and their answers. The parallel repetition of the game is the game in which the referee samples n independent pairs of questions and sends… (More)

- Anup Rao
- SIAM J. Comput.
- 2006

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>γ</sup> for an arbitrarily small constant γ > 0. Our extractor is obtained by composing seeded extractors in simple ways. We… (More)

- Anup Rao
- 2009 24th Annual IEEE Conference on Computational…
- 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)

- Mark Braverman, Anup Rao
- 2010

We show that it is possible to encode any communication protocol between two parties so that the protocol succeeds even if a (1/4 − ǫ) fraction of all symbols transmitted by the parties are corrupted adversarially, at a cost of increasing the communication in the protocol by a constant factor (the constant depends on epsilon). This encoding uses a constant… (More)

- Jesse Kamp, Anup Rao, Salil P. Vadhan, David Zuckerman
- STOC
- 2006

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 δ>0, we can extract .99 δ n bits that are exponentially close to uniform (in variation distance) from space s… (More)

- Peter Chin, Anup Rao, Van H. Vu
- ArXiv
- 2015

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)

- Boaz Barak, Mark Braverman, Xi Chen, Anup Rao
- STOC
- 2010

We describe new ways to simulate 2-party communication protocols to get protocols with potentially smaller communication. We show that every communication protocol that communicates C bits and reveals I bits of information about the inputs to the participating parties can be simulated by a new protocol involving at most ~O(√CI) bits of communication.… (More)

- Mark Braverman, Anup Rao
- IEEE Transactions on Information Theory
- 2011

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)

- Boaz Barak, Anup Rao, Ronen Shaltiel, Avi Wigderson
- STOC
- 2006

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)

- Boaz Barak, Moritz Hardt, Ishay Haviv, Anup Rao, Oded Regev, David Steurer
- 2008 49th Annual IEEE Symposium on Foundations of…
- 2008

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)