ABSTRACT
Tensors are higher-order, multiway generalizations of matrices. Many datasets in machine learning problems can be naturally organized in tensor form, and leveraging this multilinear structure usually leads to better results, since it makes use of additional information within the data that would otherwise be neglected. For this reason, tensor methods have seen a surge of interest in recent years and have become increasingly common in bioinformatics. This survey aims at providing a brief introduction to the main mathematical tools used to handle tensors, along with an overview of many biomedical areas in which these ideas have found fruitful applications in recent years.
