Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods Lecture: 1 The Singular Value Decomposition Instructor: Sham Kakade

Source URL: stat.wharton.upenn.edu

Sampling Algorithms to Update Truncated SVD Ichitaro Yamazaki, Stanimire Tomov, and Jack Dongarra University of Tennessee, Knoxville, Tennessee, U.S.A. Abstract— A truncated singular value decomposition (SVD) is a powe

Source URL: icl.cs.utk.edu

Orthogonal Matrices and the Singular Value Decomposition Carlo Tomasi The first Section below extends to m × n matrices the results on orthogonality and projection we have previously seen for vectors. The Sections there

Source URL: www.cs.duke.edu

Using Singular Value Decomposition to Parameterize State-Dependent Model Errors Christopher M. Danforth∗ Department of Mathematics and Statistics, University of Vermont Burlington, VTEugenia Kalnay

Source URL: www.weatherchaos.umd.edu

CS168: The Modern Algorithmic Toolbox Lecture #9: The Singular Value Decomposition (SVD) and Low-Rank Matrix Approximations Tim Roughgarden & Gregory Valiant∗ April 25, 2016

Source URL: theory.stanford.edu

Spectral Graph Theory and Applications WSProblem Set 1 Due: Nov. 25

Source URL: resources.mpi-inf.mpg.de

• Algebra
• Mathematics
• Graph theory
• Matrix theory
• Algebraic graph theory
• Linear algebra
• Eigenvalues and eigenvectors
• Singular value decomposition
• Laplacian matrix
• PerronFrobenius theorem
• Lovsz number

103 Documenta Math. Dynamical Symmetries in Supersymmetric Matrix1

Source URL: documenta.sagemath.org

• Algebra
• Spectral theory
• Linear algebra
• Abstract algebra
• Eigenvalues and eigenvectors
• Singular value decomposition
• Spectrum
• Spectral theory of ordinary differential equations

Microsoft Word - Structures2007SysID-Submitted.doc

Source URL: nees.ucla.edu

• Algebra
• Mechanics
• Mathematics
• Singular value decomposition
• Structural analysis
• Finite element method
• Seismology
• Continuum mechanics
• Vibration
• Seismic noise
• Eigenvalues and eigenvectors
• Normal mode

SPECTRAL ANALYSIS OF NON-HERMITIAN MATRICES MATHEMATICAL PHYSICS 2010 MATTHEW COUDRON, AMALIA CULIUC, PHILIP VU, STEPHEN WEBSTER

Source URL: sites.williams.edu

• Algebra
• Linear algebra
• Mathematics
• Matrices
• Matrix theory
• Singular value decomposition
• Mathematical physics
• Matrix
• Hermitian matrix
• Eigenvalues and eigenvectors
• Diagonalizable matrix
• Diagonal matrix

To appear in Neural Computation Methods for Binary Multidimensional Scaling Douglas L. T. Rohde School of Computer Science, Carnegie Mellon University, and the Center for the Neural Basis of Cognition

Source URL: tedlab.mit.edu

• Algebra
• Mathematics
• Linear algebra
• Vectors
• Multivariate statistics
• Matrix theory
• Abstract algebra
• Multidimensional scaling
• Singular value decomposition
• Euclidean vector
• Principal component analysis
• Latent semantic analysis