Collecting comprehensive data sets of the same subject has become a standard in
neuroscience research and uncovering multivariate relationships among collected data sets …

In the past years, network theory has successfully characterized the interaction among the
constituents of a variety of complex systems, ranging from biological to technological, and …

Reconfigurable Intelligent Surfaces (RISs) have been recently considered as an energy-
efficient solution for future wireless networks due to their fast and low-power configuration …

Knowledge graphs are structured representations of real world facts. However, they typically
contain only a small subset of all possible facts. Link prediction is a task of inferring missing …

Abstract Corona virus disease (COVID-19) acknowledged as a pandemic by the WHO and
mankind all over the world is vulnerable to this virus. Alternative tools are needed that can …

Partial Least Squares (PLS) is an estimation method and an algorithm for latent variable
path (LVP) models. PLS is a component technique and estimates the latent variables as …

Tensor completion is a problem of filling the missing or unobserved entries of partially
observed tensors. Due to the multidimensional character of tensors in describing complex …

Comprehensive and comprehensible, this classic text covers the basic and advanced topics
essential for using factor analysis as a scientific tool in psychology, education, sociology …

This survey provides an overview of higher-order tensor decompositions, their applications,
and available software. A tensor is a multidimensional or-way array. Decompositions of …

In marketing applications of structural equation models with unobservable variables,
researchers have relied almost exclusively on LISREL for parameter estimation. Apparently …