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Lecture
Matrix Computations: Complexity and Algorithms
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Related lectures (47)
Linear Systems: Direct Methods
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Covers the formulation of linear systems, direct and iterative methods for solving them, and the cost of LU factorization.
Iterative Methods: Linear Systems
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Explores iterative methods for solving linear systems, including Jacobi and Gauss-Seidel methods, Cholesky factorization, and preconditioned conjugate gradient.
Singular Value Decomposition: Applications and Interpretation
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Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.
Linear Systems: Direct and Iterative Methods
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Explores linear systems, covering direct and iterative methods for solving them with a focus on round-off errors and Richardson's algorithm.
Matrix Inversion: Basics and Properties
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Covers the basics of matrix inversion, properties of matrix multiplication, and the uniqueness of matrix inverses.
Linear Systems: Diagonal and Triangular Matrices, LU Factorization
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Covers linear systems, diagonal and triangular matrices, and LU factorization.
Matrix Multiplication: Applications and Properties
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Covers matrix multiplication, properties, and inverses in linear algebra.
Linear Systems: Triangular Matrices
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Focuses on transforming linear systems into triangular matrices to simplify the process of finding solutions.
Jacobi and Gauss-Seidel methods
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Explains the Jacobi and Gauss-Seidel methods for solving linear systems iteratively.
Richardson Method: Preconditioned Iterative Solvers
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Covers the Richardson method for solving linear systems with preconditioned iterative solvers and introduces the gradient method.
Linear Algebra: Inverse Matrix and Systems Resolution
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Covers the concept of inverse matrices and systems resolution, including the conditions for matrix invertibility and the Gauss-Jordan algorithm.
Matrix Arithmetic: Properties and Operations
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Explores matrix arithmetic, including properties, products, and dimensions, with a focus on matrix multiplication and commutativity.
Eigenvalues of Matrices: Properties and Relations
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Explores properties and relations of eigenvalues of square matrices and their products.
Matrix Operations: Partitions and Blocks
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Covers matrix operations, including partitioning and block multiplication.
Gaussian Elimination Method
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Explains the Gaussian elimination method for solving linear equations through row operations and pivoting.
Matrix Multiplication: Properties and Applications
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Explores matrix multiplication, its properties, and applications in linear maps.
Linear Algebra: Vector Spaces and Linear Independence
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Covers vector spaces, operations, and linear independence with examples from polynomials and functions.
Row Echelon Form: Gauss-Jordan Algorithm
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Covers row echelon forms and the Gauss-Jordan algorithm for solving linear systems.
Matrix Operations and Vector Spaces
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Covers elementary matrix operations and vector spaces, including properties and conditions for invertibility.
Least Squares Solutions
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Covers least squares solutions for linear systems using matrix operations and normal systems, illustrated with examples.
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