Lectures related to Linear Algebra Basics

Explores constraints, efficiency, and complexity in linear algebra, emphasizing convexity and worst-case complexity in algorithm analysis.

Covers linear applications, matrices, transformations, and the principle of superposition.

Covers bases, linear dependencies, injective and surjective transformations, and matrix representation in linear algebra.

Introduces Manopt, a toolbox for optimization on manifolds, focusing on solving optimization problems on smooth manifolds using the Matlab version.