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Dimension reduction
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#	Item
51	CS168: The Modern Algorithmic Toolbox Lecture #7: Understanding and Using Principal Component Analysis (PCA) Tim Roughgarden & Gregory Valiant∗ April 18, 2016 Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2016-06-04 09:49:44 Multivariate statistics Dimension reduction Abstract algebra Linear algebra Analytic geometry Principal component analysis Dimensionality reduction Eigenvalues and eigenvectors Linear regression Euclidean vector Degrees of freedom Eigenface
52	DSP: Robust Semi-Supervised Dimensionality Reduction using Dual Subspace Projections Su Yan∗ Sofien Bouaziz Dongwon Lee IBM Almaden Research Center Ecole Polytechnique F´ed´erale de Lausanne Pennsylvania State Univer Add to Reading List Source URL: sofienbouaziz.com Language: English - Date: 2015-11-19 01:50:34 Multivariate statistics Dimension reduction Geostatistics Functional analysis Linear algebra Dimensionality reduction Principal component analysis Nonlinear dimensionality reduction K-nearest neighbors algorithm Cluster analysis Kernel method Linear discriminant analysis
53	Towards Effective Indexing for Very Large Video Sequence Database Heng Tao Shen Beng Chin Ooi Add to Reading List Source URL: www.comp.nus.edu.sg Language: English - Date: 2005-04-04 23:21:27 Search algorithms Data mining Dimension reduction Cluster analysis Geostatistics IDistance K-means clustering Similarity N-sphere K-nearest neighbors algorithm Principal component analysis Hypersphere
54	Genome Informatics 15(2): 131–Recovering Genetic Regulatory Networks from Micro-Array Data and Location Analysis Data Add to Reading List Source URL: www.jsbi.org Language: English - Date: 2004-12-20 01:22:45 Gene expression Networks Cybernetics Dimension reduction Feature selection Model selection Algorithm Gene regulatory network DNA microarray Bayesian network Regression analysis Machine learning
55	LOCOCODE versus PCA and ICA Sepp Hochreiter Technische Universitat MunchenMunchen, Germany Add to Reading List Source URL: www.bioinf.jku.at Language: English - Date: 2013-01-23 02:18:32 Multivariate statistics Artificial neural networks Signal processing Dimension reduction Computational neuroscience Principal component analysis Independent component analysis Sepp Hochreiter Autoencoder Backpropagation
56	NONLINEAR ICA THROUGH LOW-COMPLEXITY AUTOENCODERS Sepp Hochreiter J¨urgen Schmidhuber Fakult¨at f¨ur Informatik Add to Reading List Source URL: www.bioinf.jku.at Language: English - Date: 2013-01-23 02:21:57 Multivariate statistics Artificial neural networks Signal processing Dimension reduction Computational neuroscience Independent component analysis Factorial code Principal component analysis Machine learning Self-organizing map Sepp Hochreiter Deep learning
57	Incremental Learning for Robust Visual Tracking ∗ David A. Ross∗ Jongwoo Lim† Ruei-Sung Lin‡ Ming-Hsuan Yang† University of Toronto † Honda Research Institute, USA ‡ Motorola Labs Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2007-08-14 20:46:19 Linear algebra Multivariate statistics Matrix theory Dimension reduction Numerical linear algebra Singular value decomposition Covariance Principal component analysis Normal distribution Kalman filter Linear discriminant analysis Eigenvalues and eigenvectors
58	CMBver9-Baran_2P 1..13 Add to Reading List Source URL: www.cs.tau.ac.il Language: English - Date: 2015-06-23 04:28:22 Genetics Covariance and correlation Multivariate statistics Population genetics Dimension reduction Principal component analysis Genetic variance Covariance Genome-wide association study Single-nucleotide polymorphism Imputation Eigenvalues and eigenvectors
59	ISSN No: International Journal & Magazine of Engineering, Technology, Management and Research A Peer Reviewed Open Access International Journal Add to Reading List Source URL: www.ijmetmr.com Language: English - Date: 2015-06-10 07:44:40 Dimension reduction Machine learning Statistical classification Multivariate statistics Naive Bayes classifier Pattern recognition Random projection Nonlinear dimensionality reduction Principal component analysis Matrix JohnsonLindenstrauss lemma Compressed sensing
60	Unsupervised Dimensionality Estimation and Manifold Learning in high-dimensional Spaces by Tensor Voting Philippos Mordohai and G´erard Medioni University of Southern California email: {mordohai,medioni}@iris.usc.edu Add to Reading List Source URL: www.cs.stevens.edu Language: English - Date: 2007-08-16 15:43:24 Multivariate statistics Dimension reduction Riemannian geometry Machine learning Computational statistics Tensor Nonlinear dimensionality reduction Dimensionality reduction Isomap LaplaceBeltrami operator Manifold Metric tensor

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