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6.S955: Applied Numerical Algorithms (fall 2023)

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Applied Numerical Algorithms, fall 2023 (lecture 15): Constrained optimization, KKT conditions

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Applied Numerical Algorithms, fall 2023 (lecture 14): BFGS, DFP, Quasi-Newton optimization

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Applied Numerical Algorithms, fall 2023 (lecture 13): Gradient descent, line search

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Applied Numerical Algorithms, fall 2023 (lecture 12): Broyden low-rank updates, 1D optimization

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Applied Numerical Algorithms, fall 2023 (lecture 11): Root-finding, Newton's/Broyden's methods

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Applied Numerical Algorithms, fall 2023 (lecture 10): Applications of SVD; Procrustes problem

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Applied Numerical Algorithms, fall 2023 (lecture 9): QR iteration, SVD

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Applied Numerical Algorithms, fall 2023 (lecture 8): Eigenvalue iteration, deflation

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Applied Numerical Algorithms, fall 2023 (lecture 7): Applications of eigenvectors

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Applied Numerical Algorithms, fall 2023 (lecture 6): QR factorization

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Applied Numerical Algorithms, fall 2023 (lecture 5): Condition number for linear systems

Applied Numerical Algorithms, fall 2023 (lecture 4): Cholesky factorization, sparse matrices

Applied Numerical Algorithms, fall 2023 (lecture 3): LU factorization, designing linear systems

Applied Numerical Algorithms, fall 2023 (lecture 2): Conditioning, linear systems, Gaussian elim.

Applied Numerical Algorithms, fall 2023 (lecture 1): Introduction, number systems, measuring error