Lectures related to Stationary Points and Saddle Points

Provides an overview of symmetric matrices, quadratic forms, and their applications in linear algebra and analysis.

Explores the Spectral Theorem, emphasizing the Min-Max Criterion for symmetric matrices and the properties of positive definite matrices.

Covers the decomposition of matrices into triangular blocks and spectral decomposition.

Covers the properties of symmetric matrices, orthogonal matrices, and eigenvalues.

Covers the concept of symmetric matrices, orthogonal bases, and eigenvectors.

Explores spectral and singular value decompositions of matrices.

Covers the calculation of eigenvalues and eigenvectors, emphasizing their significance and applications.

Explores the diagonalizability of symmetric matrices and their eigenvectors in an orthonormal basis.