Contents 1 Introduction

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Date: 2012-02-14 13:20:00 Abstract algebra Euclidean vector Principal component analysis Vector space Dimension Singular value decomposition Matrix N-sphere Nearest neighbor search Algebra Mathematics Linear algebra		Contents 1 Introduction Add to Reading List Source URL: www.cs.cmu.edu Download Document from Source Website File Size: 1,83 MB Share Document on Facebook

	Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods Lecture: 1 The Singular Value Decomposition Instructor: Sham Kakade DocID: 1vbS6 - View Document
	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 DocID: 1udU9 - View Document
	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 DocID: 1tr0F - View Document
	Using Singular Value Decomposition to Parameterize State-Dependent Model Errors Christopher M. Danforth∗ Department of Mathematics and Statistics, University of Vermont Burlington, VTEugenia Kalnay DocID: 1tjbW - View Document
	CS168: The Modern Algorithmic Toolbox Lecture #9: The Singular Value Decomposition (SVD) and Low-Rank Matrix Approximations Tim Roughgarden & Gregory Valiant∗ April 25, 2016 DocID: 1rHEk - View Document