CEest.m
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Estimates the probability that the minimum of independent beta random variables is greater
than a given threshold via CE. Uses minbeta.m.
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CESAT.m
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Solves a SAT problem via CE. Uses sC.c (must be compiled first). SATdata.mat contains the example used in the book.
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minbeta.m
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Given a matrix, returns the smallest element in each row.
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MLE (folder)
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Computes the MLE for Dirichlet data via the CE method.
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peaks (folder)
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Contains examples of the CE method for optimization of the non-noisy and the noisy peaks function.
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SATdata.mat
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Contains the SAT instance used in the book. Load into the workspace via "load SATdata.mat".
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sC.c
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Evaluates the SAT score function efficiently, given a *sparse* matrix. Must first be compiled within Matlab, using "mex sC.c".
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