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Eigenvalues and eigenvectors
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#	Item
581	On-line Estimation of Visual-Motor Models using Active Vision Martin J¨agersand, Randal Nelson Department of Computer Science, University of Rochester, Rochester, NYfjag, http://www.cs.ro Add to Reading List Source URL: www.cs.rochester.edu Language: English - Date: 1996-02-25 20:50:43 Singular value decomposition Robot control Computer vision Robotic sensing Visual Servoing Multivariate statistics Principal component analysis Jacobian matrix and determinant Eigenvalues and eigenvectors Algebra Linear algebra Mathematics
582	Appears in the Second International Conference on Audio- and Video-based Biometric Person Authentication, AVBPA’99, Washington D. C. USA, March 22-24, Comparative Assessment of Independent Component Analysis (IC Add to Reading List Source URL: www.face-rec.org Language: English - Date: 2004-08-31 03:42:36 Statistical classification Data analysis Singular value decomposition Linear discriminant analysis Principal component analysis Independent component analysis Eigenvalues and eigenvectors Eigenface Pattern recognition Statistics Multivariate statistics Machine learning
583	Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps R. R. Coifman†, S. Lafon, A. B. Lee, M. Maggioni, B. Nadler, F. Warner, and S. W. Zucker‡ Department of Mat Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English* - Date: 2006-02-15 16:01:29 Linear algebra Multivariable calculus Differential operators Fourier analysis Stochastic differential equations Nonlinear dimensionality reduction Laplace operator Heat equation Eigenvalues and eigenvectors Mathematical analysis Mathematics Calculus
584	Determining the number of components in a factor model from limited noisy data Shira Kritchman and Boaz Nadler1 Department of Computer Science and Applied Mathematics Weizmann Institute of Science, P.O.Box 26, Rehovot 76 Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2008-06-03 18:16:22 Data analysis Covariance and correlation Singular value decomposition Mathematical physics Summary statistics Multivariate normal distribution Principal component analysis Eigenvalues and eigenvectors Covariance matrix Statistics Algebra Mathematics
585	Supplement Figure S1. Vertical profiles of the square roots of the diagonal elements of the covariance matrices C for different latitude bins in the southern (left) and northern (right) hemispheres. These quantities are Add to Reading List Source URL: www.atmos-meas-tech.net Language: English - Date: 2014-12-03 11:49:56 Covariance and correlation Data analysis Singular value decomposition Matrices Summary statistics Ozone depletion Correlation and dependence Eigenvalues and eigenvectors Covariance matrix Algebra Statistics Mathematics
586	REFINED PERTURBATION BOUNDS FOR EIGENVALUES OF HERMITIAN AND NON-HERMITIAN MATRICES∗ I.C.F. IPSEN† AND B. NADLER‡ Abstract. We present eigenvalue bounds for perturbations of Hermitian matrices, and express the chan Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2007-12-27 05:12:46 Matrix theory Matrices Singular value decomposition Spectral theory Eigenvalues and eigenvectors Eigendecomposition of a matrix Hermitian matrix Diagonalizable matrix Bauer–Fike theorem Algebra Linear algebra Mathematics
587	Fundamental Limitations of Spectral Clustering Boaz Nadler∗, Meirav Galun Department of Applied Mathematics and Computer Science Weizmann Institute of Science, Rehovot, Israelboaz.nadler,meirav.galun@weizmann.a Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2006-12-10 07:58:37 Singular value decomposition Cluster analysis Spectral clustering Information bottleneck method Eigenvalues and eigenvectors Principal component analysis Segmentation K-means clustering Graph partition Statistics Multivariate statistics Data analysis
588	Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators Boaz Nadler∗ St´ephane Lafon Ronald R. Coifman Department of Mathematics, Yale University, New Haven, CT 06520. {boaz.nadler,stephane.l Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2006-05-04 10:36:46 Multivariate statistics Singular value decomposition Matrix theory Linear algebra Markov processes Eigenvalues and eigenvectors Principal component analysis Heat equation Information bottleneck method Algebra Mathematics Statistics
589	Determining the number of components in a factor model from limited noisy data Shira Kritchman and Boaz Nadler1 Department of Computer Science and Applied Mathematics Weizmann Institute of Science, P.O.Box 26, Rehovot 76 Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2008-06-03 18:16:22 Data analysis Covariance and correlation Singular value decomposition Mathematical physics Summary statistics Multivariate normal distribution Principal component analysis Eigenvalues and eigenvectors Covariance matrix Statistics Algebra Mathematics
590	DO SEMIDEFINITE RELAXATIONS REALLY SOLVE SPARSE PCA? arXiv:1306.3690v1 [math.ST] 16 JunBy Robert Krauthgamer Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-06-17 20:40:45 Data analysis Singular value decomposition Matrices Covariance and correlation Linear algebra Principal component analysis Multivariate normal distribution Covariance matrix Eigenvalues and eigenvectors Statistics Algebra Mathematics

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