This lecture covers the norm of a matrix, operator, singular values, unitary matrices, and decomposition. It explains the concept of rank, 2-norm, and basis in linear algebra.
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Provides a review of linear algebra concepts crucial for convex optimization, covering topics such as vector norms, eigenvalues, and positive semidefinite matrices.
