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