We consider the problem of extracting randomness from sources that are efficiently samplable, in the sense that each output bit of the sampler only depends on some small number d ...
A new "herding" algorithm is proposed which directly converts observed moments into a sequence of pseudo-samples. The pseudosamples respect the moment constraints and ma...
This is the sample implementation of a Markov random field based color image segmentation algorithm described in the following paper:
Zoltan Kato, Ting Chuen Pong, and John Chu...
We propose an algorithm for recovering the matrix A in X = AS where X is a random vector of lower dimension than S. S is assumed to be sparse in the sense that S has less nonzero e...
Fabian J. Theis, Pando G. Georgiev, Andrzej Cichoc...
The objective of this paper is twofold. First, the problem of generation of real random matrix samples with uniform distribution in structured (spectral) norm bounded sets is stud...