Sparse matrix

Related lectures (29)

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Explores binary spiked matrix estimation, analyzing consistent equations and Bayesian estimators.

Explores the complexity of matrix computations, focusing on low rank approximation algorithms and their applications.

Covers the basics of Fourier transform and the significance of fixed angular momentum states in mass calculations.

Explains the QR factorization theorem and demonstrates the Gram-Schmidt procedure with an example.

Explores eigenvalues, ladder operations, and quantum number values in quantum physics.

Explores roughness penalty, band matrices, and Bayesian inference in regression smoothing.

Explores numerical methods for flow simulation, including finite element, spectral, particle, and lattice Boltzmann methods.

Covers optimal distributed control using Gradient Descent to achieve locally optimal controllers in large-scale systems.

Covers correlation functions, Franck-Condon transitions, Born-Oppenheimer approximation, and spectra.