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Dimension reduction
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41	ALGORITHMIC LINEAR DIMENSION REDUCTION IN THE `1 NORM FOR SPARSE VECTORS A. C. GILBERT, M. J. STRAUSS, J. A. TROPP, AND R. VERSHYNIN Abstract. We can recover approximately a sparse signal with limited noise, i.e, a vecto Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2009-02-03 14:30:47 Digital signal processing Computational complexity theory Matrix Fast Fourier transform Time complexity Mathematics Computer science Theoretical computer science Polynomials
42	Proceedings of ARPA Image Understanding Workshop Monterey, NovemberSoftware Library for Appearance Matching (SLAM) * Sameer A. Nene, Shree K. Nayar and Hiroshi Murase Center for Research in Intelligent Systems, De Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2005-07-11 00:33:12 Algebra Mathematics Linear algebra Dimension reduction Multivariate statistics Matrix theory Machine learning Eigenvalues and eigenvectors Vector space Principal component analysis Eigenface Pattern recognition
43	Clustered factor analysis of multineuronal spike data Lars Buesing1 , Timothy A. Machado1,2 , John P. Cunningham1 and Liam Paninski1 1 Department of Statistics, Center for Theoretical Neuroscience & Grossman Center for Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2014-10-13 19:51:15 Statistics Applied mathematics Machine learning Cluster analysis Cybernetics Dimension reduction Computational neuroscience Mixture model K-means clustering Expectationmaximization algorithm Principal component analysis Artificial neural network
44	DATA QUALITY IMPLICATIONS OF RASTER GENERALIZATION Howard Veregin and Robert McMaster Department of Geography University of Minnesota 267-19thAveS,Rm414 Add to Reading List Source URL: mapcontext.com Language: English - Date: 2008-08-29 22:34:06 Machine learning Matrix Statistical classification Geographic information system Multivariate statistics Dimension reduction
45	Discussion of “Spectral Dimensionality Reduction via Maximum Entropy” Laurens van der Maaten Delft University of Technology Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Multivariate statistics Dimension reduction Computational statistics Machine learning Dimension Nonlinear dimensionality reduction Dimensionality reduction Isomap Semidefinite embedding Spectral clustering Kernel principal component analysis T-distributed stochastic neighbor embedding
46	From Web to Map: Exploring the World of Music Olga Goussevskaia ETH Zurich, Switzerland Michael Kuhn Add to Reading List Source URL: disco.ethz.ch Language: English - Date: 2014-09-26 08:36:35 Topological graph theory Graph drawing Dimension Dimension reduction Nonlinear dimensionality reduction Graph embedding Force-directed graph drawing
47	An Interactive Visual Testbed System for Dimension Reduction and Clustering of Large-scale High-dimensional Data Jaegul Choo, Hanseung Lee, Zhicheng Liu, John Stasko, and Haesun Park Georgia Institute of Technology, USA Add to Reading List Source URL: www.zcliu.org Language: English - Date: 2016-07-30 20:21:03 Visualization Multivariate statistics Dimension reduction Data Data visualization Information technology governance K-means clustering Parallel coordinates Principal component analysis Information visualization Spectral clustering Data analysis
48	Multi-objective Genetic Programming for Visual Analytics Ilknur Icke1 and Andrew Rosenberg1,2 1 The Graduate Center, The City University of New York, Add to Reading List Source URL: eniac.cs.qc.cuny.edu Language: English - Date: 2011-03-10 09:53:36 Multivariate statistics Dimension reduction Statistical classification Machine learning Principal component analysis Dimensionality reduction K-nearest neighbors algorithm Feature extraction Curse of dimensionality Linear discriminant analysis Multidimensional scaling Kernel principal component analysis
49	Tilburg centre for Creative Computing Tilburg University http://www.uvt.nl/ticc P.O. BoxLE Tilburg, The Netherlands Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Multivariate statistics Dimension reduction Machine learning Computational statistics Dimension Nonlinear dimensionality reduction Dimensionality reduction Isomap Principal component analysis Kernel principal component analysis Semidefinite embedding Kernel method