Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Convex Optimization: Notation and Matrix Norms
Graph Chatbot
Related lectures (46)
Linear Operators: Basis Transformation and Eigenvalues
Explores basis transformation, eigenvalues, and linear operators in inner product spaces, emphasizing their significance in Quantum Mechanics.
Linear Algebra Review
Covers the basics of linear algebra, including matrix operations and singular value decomposition.
Linear Independence and Basis
Explains linear independence, basis, and matrix rank with examples and exercises.
Linear Algebra: Matrices Properties
Explores properties of 3x3 matrices with real coefficients and determinant calculation methods.
Diagonalization of Linear Transformations
Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.
Diagonalization of Linear Transformations
Covers the diagonalization of linear transformations in R^3, exploring properties and examples.
Convex Optimization: Linear Algebra Review
Log in to Mediaspace to watch this video
Provides a review of linear algebra concepts crucial for convex optimization, covering topics such as vector norms, eigenvalues, and positive semidefinite matrices.
Linear Algebra Review: Convex Optimization
Log in to Mediaspace to watch this video
Covers essential linear algebra concepts for convex optimization, including vector norms, eigenvalue decomposition, and matrix properties.
Characteristic Polynomials and Similar Matrices
Log in to Mediaspace to watch this video
Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.
Linear Algebra Basics
Log in to Mediaspace to watch this video
Covers fundamental concepts in linear algebra, including linear equations, matrix operations, determinants, and vector spaces.
Matrix Similarity and Diagonalization
Log in to Mediaspace to watch this video
Explores matrix similarity, diagonalization, characteristic polynomials, eigenvalues, and eigenvectors in linear algebra.
Matrix Operations: Linear Systems and Solutions
Log in to Mediaspace to watch this video
Explores matrix operations, linear systems, solutions, and the span of vectors in linear algebra.
Eigenvalues and Eigenvectors Decomposition
Log in to Mediaspace to watch this video
Covers the decomposition of a matrix into its eigenvalues and eigenvectors, the orthogonality of eigenvectors, and the normalization of vectors.
Characterization of Invertible Matrices
Log in to Mediaspace to watch this video
Explores the properties of invertible matrices, including unique solutions and linear independence.
Physics 1: Vectors and Dot Product
Log in to Mediaspace to watch this video
Covers the properties of vectors, including commutativity, distributivity, and linearity.
Diagonalization of Matrices: Theory and Examples
Log in to Mediaspace to watch this video
Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.
Singular Value Decomposition: Applications and Interpretation
Log in to Mediaspace to watch this video
Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.
Linear Applications and Eigenvectors
Log in to Mediaspace to watch this video
Covers linear applications, diagonalizable matrices, eigenvectors, and orthogonal subspaces in R^n.
Linear Equations: Vectors and Matrices
Log in to Mediaspace to watch this video
Covers linear equations, vectors, and matrices, exploring their fundamental concepts and applications.
Singular Value Decomposition: Orthogonal Vectors and Matrix Decomposition
Log in to Mediaspace to watch this video
Explains Singular Value Decomposition, focusing on orthogonal vectors and matrix decomposition.
Previous
Page 1 of 3
Next
