Gram matrix

Related lectures (11)

Explores Kernel K-means algorithm, its analysis, applications, and limitations in clustering.

Presents solutions to exercises on Canonical Correlation Analysis, exploring correlation, Gram matrices, kernel matrices, and vector properties.

Covers the determinant of a matrix, factorization, and linear equations with infinite solutions.

Explores matrix determinant properties, inverse, transpose, and applications in solving equations.

Covers the properties and calculations of matrix determinants, including special cases and examples.

Covers controllability and observability in linear systems, discussing necessary conditions and implications of unimodular matrices.

Explores lattices in Rd, Gram matrices, theta functions, and modular properties.

Explores stability in linear 2D systems, covering fixed points, vector fields, and phase portraits.

Explores matrix determinant properties, quick calculations, and geometric interpretation in vector spaces.

Covers the properties of matrix determinants and strategies for their calculation.

Covers linear models like Ridge, OLS, and LASSO, explaining singular values and regression analysis.

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