Lectures related to Matrix Computations: Low Rank Approximation

Covers matrix product, inverses, and properties of invertible matrices.

Covers linear systems, diagonal and triangular matrices, and LU factorization.

Covers the basics of matrix inversion, properties of matrix multiplication, and the uniqueness of matrix inverses.

Explores the Divide-and-Conquer algorithm for matrix multiplication, including Strassen's Method and its significance in optimizing time complexity.

Discusses Strassen's algorithm for matrix multiplication and heaps, covering efficient algorithms and their applications in computer science.

Explores the unique decomposition of matrices into diagonalizable and nilpotent parts, showcasing their properties and applications.