Recent advancements in data-driven process control and performance analysis could
provide the wastewater treatment industry with an opportunity to reduce costs and improve …

Abstract Multivariate Curve Resolution (MCR) covers a wide span of algorithms designed to
tackle the mixture analysis problem by expressing the original data through a bilinear model …

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 …

Most algorithms for representation learning and link prediction in relational data have been
designed for static data. However, the data they are applied to usually evolves with time …

We present the R package missMDA which performs principal component methods on
incomplete data sets, aiming to obtain scores, loadings and graphical representations …

Tensors, or multidimensional arrays, are data structures that can naturally represent visual
data of multiple dimensions. Inherently able to efficiently capture structured, latent semantic …

In various disciplines, information about the same phenomenon can be acquired from
different types of detectors, at different conditions, in multiple experiments or subjects …

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

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 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 …