Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
In a recent paper we introduced a modification of the adaptive beamformer orthogonal rejection test (ABORT) for adaptive detection of signals in unknown noise, by supposing under t...
Francesco Bandiera, Olivier Besson, Danilo Orlando...
Recent evidence suggests that some characteristics of computer and telecommunications systems may be well described using heavy tailed distributions — distributions whose tail d...