Tensor Decompositions - A Quick Tour of Illustrative Applications

Explore the fundamentals and applications of tensor decompositions in this comprehensive 1-hour 11-minute lecture from the Society for Industrial and Applied Mathematics. Delve into the Tucker, Canonical Polyadic (CP), and Generalized CP (GCP) decompositions, focusing on their use as tools for unsupervised learning. Discover how tensor decompositions are applied across diverse fields such as neuroscience, market segmentation, hyperspectral image processing, network science, financial portfolio allocation, deep learning, quantum information theory, reinforcement learning, computer vision, drug design, energy demand forecasting, and reduced-order models. Walk through real-world dataset examples, gaining hands-on experience with existing software and result analysis. Suitable for both novices and experts, this lecture provides valuable insights into tensor decomposition applications and offers resources for future classroom projects.