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Lecture Recordings: Numerical Linear Algebra
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Corso di Laurea Magistrale in Informatica (LM-18)
CM24
Lecture Recordings: Numerical Linear Algebra
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Lectures Recordings: Optimization
Select activity 2024-09-19: Recap of linear algebra: linear combinations, matrix products, coordinates
2024-09-19: Recap of linear algebra: linear combinations, matrix products, coordinates
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Select activity l1
l1
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Select activity 2024-09-20: Orthogonality, eigenvectors, positive definiteness and semidefiniteness
2024-09-20: Orthogonality, eigenvectors, positive definiteness and semidefiniteness
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Select activity l2
l2
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Select activity 2024-09-27: introduction to least squares problems. Some applications: linear estimation, polynomial fitting. Uniqueness of solution. Method of normal equations. Pseudoinverse.
2024-09-27: introduction to least squares problems. Some applications: linear estimation, polynomial fitting. Uniqueness of solution. Method of normal equations. Pseudoinverse.
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Select activity l3
l3
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Select activity 2024-10-02: Singular value decomposition. Matrix norms. Eckhart-Young theorem (statement)
2024-10-02: Singular value decomposition. Matrix norms. Eckhart-Young theorem (statement)
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Select activity l4
l4
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Select activity 2024-10-04: sparse matrices. Conjugate gradient: introduction, subspace optimality properties. Krylov subspaces and their relation to gradient-type methods.
2024-10-04: sparse matrices. Conjugate gradient: introduction, subspace optimality properties. Krylov subspaces and their relation to gradient-type methods.
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Select activity l5
l5
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Select activity 2024-10-16: Q-norm; orthogonality and convergence properties of CG (convergence in terms of polynomial approximation, worst-case bound, both without proof)
2024-10-16: Q-norm; orthogonality and convergence properties of CG (convergence in terms of polynomial approximation, worst-case bound, both without proof)
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Select activity l6
l6
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Select activity 2024-10-18: convergence of CG and polynomial approximation. Data analysis with the SVD: images, student scores, text (latent semantic analysis)
2024-10-18: convergence of CG and polynomial approximation. Data analysis with the SVD: images, student scores, text (latent semantic analysis)
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Select activity l7
l7
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Select activity 2024-10-25: dimensionality reduction with PCA; PCA of the Yale faces dataset, used also for image recognition
2024-10-25: dimensionality reduction with PCA; PCA of the Yale faces dataset, used also for image recognition
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Select activity l8
l8
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Select activity 2024-10-30: Householder reflectors. QR factorization. Different ways to handle Q: thin QR, returning the Householder vectors.
2024-10-30: Householder reflectors. QR factorization. Different ways to handle Q: thin QR, returning the Householder vectors.
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Select activity l9
l9
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Select activity 2024-11-08: solving least-squares problems with the QR factorization and with the SVD. Singular least squares problems. The effect of noise; regularization via truncated SVD.
2024-11-08: solving least-squares problems with the QR factorization and with the SVD. Singular least squares problems. The effect of noise; regularization via truncated SVD.
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Select activity l10
l10
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Select activity 2024-11-13: Tikhonov regularization. Condition number. The condition number of solving linear equations and least-squares problems.
2024-11-13: Tikhonov regularization. Condition number. The condition number of solving linear equations and least-squares problems.
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Select activity l11
l11
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Select activity 2024-11-15: stability of floating point computations. Backward stability, with an example. A posteriori stability tests for linear systems and LS problems.
2024-11-15: stability of floating point computations. Backward stability, with an example. A posteriori stability tests for linear systems and LS problems.
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Select activity l12
l12
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Select activity 2024-11-22: backward stability of QR factorization. Backward stability properties of algorithms to solve LS problems and their comparison. Introduction to the Arnoldi algorithm.
2024-11-22: backward stability of QR factorization. Backward stability properties of algorithms to solve LS problems and their comparison. Introduction to the Arnoldi algorithm.
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Select activity l13
l13
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Select activity 2024-11-27: Arnoldi algorithm, GMRES. Convergence, computational and implementation remarks. The symmetric version: MINRES.
2024-11-27: Arnoldi algorithm, GMRES. Convergence, computational and implementation remarks. The symmetric version: MINRES.
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Select activity l14
l14
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Select activity 2024-12-06: overview of direct methods for linear systems: LU, LDL, Cholesky, remarks about sparsity
2024-12-06: overview of direct methods for linear systems: LU, LDL, Cholesky, remarks about sparsity
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Select activity l15
l15
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Select activity 2024-12-16: examples of solutions of large-scale linear systems. Reordering in direct methods. A quick introduction to preconditioners for iterative methods.
2024-12-16: examples of solutions of large-scale linear systems. Reordering in direct methods. A quick introduction to preconditioners for iterative methods.
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Select activity l16
l16
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