Covers the basics of tensors, including their definition, properties, and decomposition, starting with a motivating example involving Gaussian distributions.
Provides a review of linear algebra concepts crucial for convex optimization, covering topics such as vector norms, eigenvalues, and positive semidefinite matrices.
Explores the history, theory, and applications of optimal transport in various fields, showcasing its importance in solving complex mathematical problems.
