Recent advances in airborne and spaceborne hyperspectral imaging technology have
provided end users with rich spectral, spatial, and temporal information. They have made a …

Hyperspectral remote sensing is based on measuring the scattered and reflected
electromagnetic signals from the Earth's surface emitted by the Sun. The received radiance …

Tensors or multiway arrays are functions of three or more indices (i, j, k,...)-similar to matrices
(two-way arrays), which are functions of two indices (r, c) for (row, column). Tensors have a …

Modern applications in engineering and data science are increasingly based on
multidimensional data of exceedingly high volume, variety, and structural richness …

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 …

Most state-of-the-art deep neural networks are overparameterized and exhibit a high
computational cost. A straightforward approach to this problem is to replace convolutional …

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 …

Tensor networks have in recent years emerged as the powerful tools for solving the large-
scale optimization problems. One of the most popular tensor network is tensor train (TT) …

A simple nonrecursive form of the tensor decomposition in d dimensions is presented. It
does not inherently suffer from the curse of dimensionality, it has asymptotically the same …

This work considers a computationally and statistically efficient parameter estimation method
for a wide class of latent variable models—including Gaussian mixture models, hidden …