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probabilityRBP algorithm for lossy compression in reduced, ultrasparse GF(q) codes
This code implements a novel data compression technique for binary symmetric sources based on the cavity method over GF(q), the Galois Field of order q. We present a scheme of low complexity and nearoptimal empirical performance. The compression step is based on a reduction of a sparse lowdensity paritycheck code over GF(q) and is done through the socalled reinforced beliefpropagation equations. These reduced codes appear to have a nontrivial geometrical modification of the space of codewords, which makes such compression computationally feasible.
{Inference of sparse combinatorialcontrol networks from geneexpression data: a message passing approach}
{Inference of sparse combinatorialcontrol networks from geneexpression data: a message passing approach}. BMC bioinformatics. 2010;11:355.
Stochastic optimization by message passing
Stochastic optimization by message passing. JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT. 2011;2011.
Computer GoGo is an ancient Chinese game that originated some 4000 years ago and has still great popularity nowadays. Computer Go on the other hand has made little progress in these 4000 years: best go programs are rated like middletoweak amateur human players. We will discuss one recent approach to computer go [¹], based on a mixture of two relatively well known strategies: the UCT algorithm and Monte Carlo, which happens to be the most successful one to date. Reference: Date:
Wed, 04/02/2009  12:30
Speaker:
Alfredo Braunstein
