Abstract 3D imaging has become popular for analyzing material microstructures. When time
lapse series of 3D pictures are acquired during a single experiment, it is possible to …

This chapter surveys recent work in applying ideas from graphical models and message
passing algorithms to solve large-scale regularized regression problems. In particular, the …

High-dimensional probability offers insight into the behavior of random vectors, random
matrices, random subspaces, and objects used to quantify uncertainty in high dimensions …

The next wave of wireless technologies will proliferate in connecting sensors, machines, and
robots for myriad new applications, thereby creating the fabric for the Internet of Things (IoT) …

Students in statistics or data science usually learn early on that when the sample size n is
large relative to the number of variables p, fitting a logistic model by the method of maximum …

This paper considers the massive connectivity application in which a large number of
devices communicate with a base-station (BS) in a sporadic fashion. Device activity …

A denoising algorithm seeks to remove noise, errors, or perturbations from a signal.
Extensive research has been devoted to this arena over the last several decades, and as a …

We consider a model for logistic regression where only a subset of features of size is used
for training a linear classifier over training samples. The classifier is obtained by running …

“Approximate message passing”(AMP) algorithms have proved to be effective in
reconstructing sparse signals from a small number of incoherent linear measurements …

When recovering a sparse signal from noisy compressive linear measurements, the
distribution of the signal's non-zero coefficients can have a profound effect on recovery …