Improving the efficiency of algorithms for fundamental computations can have a widespread
impact, as it can affect the overall speed of a large amount of computations. Matrix …

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned
behaviors can require many days to mature. While recent experimental advances enable …

This book can be divided into five categories based on the main purposes:(1) the
development of tensor spectral theory;(2) the study of tensor complementarity problems …

Background Segmentation of gliomas in multi-parametric (MP-) MR images is challenging
due to their heterogeneous nature in terms of size, appearance and location. Manual tumor …

We theoretically study subradiant states in an array of atoms coupled to photons
propagating in a one-dimensional waveguide focusing on the strongly interacting many …

In the context of the PhysioNet/CinC 2016 Challenge, where a relatively large, labeled data
set of phonocardiograms (PCGs) was made available, this work presents a mixed approach …

The current data acquisition techniques enable the gathering and storage of extensive
datasets, encompassing multidimensional arrays. Recent researchers focus on the analysis …

The real estate market has a significant impact on people's daily life. Therefore, it is crucial to
understand the real estate market from both spatial and temporal perspectives, while there is …

During the past 20 years, low-rank tensor and matrix decomposition models (LRDMs) have
become indispensable tools for signal processing, machine learning, and data science …

Real‐life data often exhibit some structure and/or sparsity, allowing one to use parsimonious
models for compact representation and approximation. When considering matrix and tensor …