This article provides an overview of tensors, their properties, and their applications in
statistics. Tensors, also known as multidimensional arrays, are generalizations of matrices to …

Matrix theory is one of the most fundamental tools of mathematics and science, and a
number of classical books on matrix analysis have been written to explore this theory. As a …

The widespread use of multisensor technology and the emergence of big data sets have
highlighted the limitations of standard flat-view matrix models and the necessity to move …

This article presents a powerful algorithmic framework for big data optimization, called the
block successive upper-bound minimization (BSUM). The BSUM includes as special cases …

The block coordinate descent (BCD) method is widely used for minimizing a continuous
function f of several block variables. At each iteration of this method, a single block of …

This article deals with the problem of angle and incremental range (ie, the target range offset
with respect to the center of the cell under test) estimation with a frequency diverse array …

This paper is focused on the design of phase sequences with good (aperiodic)
autocorrelation properties in terms of peak sidelobe level and integrated sidelobe level. The …

Non-negative matrix factorization (NMF) has found numerous applications, due to its ability
to provide interpretable decompositions. Perhaps surprisingly, existing results regarding its …

We propose a general algorithmic framework for constrained matrix and tensor factorization,
which is widely used in signal processing and machine learning. The new framework is a …

Moment and polynomial optimization has received high attention in recent decades. It has
beautiful theory and efficient methods, as well as broad applications for various …