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Kernel methods
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#	Item
201	T O APPEAR IN N EURAL I NFORMATION P ROCESSING S YSTEMS[removed]Efficient Multiscale Sampling from Products of Gaussian Mixtures Alexander T. Ihler, Erik B. Sudderth, William T. Freeman, and Alan S. Willsky Department of E Add to Reading List Source URL: ssg.mit.edu Language: English - Date: 2012-02-01 13:34:22 Computational statistics Estimation theory Gaussian function Gibbs sampling Normal distribution Expectation–maximization algorithm Kullback–Leibler divergence Multivariate kernel density estimation Importance sampling Statistics Monte Carlo methods Non-parametric statistics
202	Package ‘kernlab’ July 2, 2014 Version[removed]Title Kernel-based Machine Learning Lab Description Kernel-based machine learning methods for classification,regression, clustering, novelty detection, quantile regressio Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 12:14:01 Linear algebra Statistical classification Numerical linear algebra Multivariate statistics Singular value decomposition Kernel Positive-definite kernel Matrix String kernel Algebra Mathematics Statistics
203	kernlab – An S4 Package for Kernel Methods in R Alexandros Karatzoglou Alex Smola Technische Universit¨ Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 12:14:01 Statistical classification Non-parametric statistics Support vector machine Kernel methods Relevance vector machine Kernel trick Kernel principal component analysis Kernel Projection Statistics Machine learning Mathematics
204	Less is More: Two- and Three-Dimensional Graphics for Data Display Leland Wilkinson SYSTAT, Inc. and Northwestern University 1800 Sherman Ave. Evanston, IL[removed]Revised version published in Behavior Research Methods, In Add to Reading List Source URL: www.cs.uic.edu Language: English - Date: 2010-02-27 00:59:50 Plot Histogram Kernel density estimation Dot plot Stemplot Box plot Chart Density estimation Local regression Statistics Data analysis Non-parametric statistics
205	Predictive low-rank decomposition for kernel methods Francis R. Bach Centre de Morphologie Math´ematique, Ecole des Mines de Paris 35 rue Saint-Honor´e, 77300 Fontainebleau, France Michael I. Jordan Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:14:49 Numerical linear algebra Matrix theory Singular value decomposition Matrices Cholesky decomposition QR decomposition Matrix decomposition Incomplete Cholesky factorization Eigendecomposition of a matrix Algebra Linear algebra Mathematics
206	Non-Monotonic Feature Selection Zenglin Xu ZLXU @ CSE . CUHK . EDU . HK Department of Computer Science & Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong Rong Jin RONGJIN @ CSE . MSU . EDU Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2009-05-18 12:16:45 Support vector machine Feature selection Algorithm Kernel methods Symbol Supervised learning Greedy algorithm Least-angle regression Statistics Machine learning Statistical classification
207	Generalized Multiview Analysis: A Discriminative Latent Space Abhishek Sharma† Abhishek Kumar Hal Daume III David W. Jacobs Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2012-10-08 15:23:23 Singular value decomposition Machine learning Computer vision Statistical classification Linear discriminant analysis Eigenface Feature extraction Kernel methods Principal component analysis Statistics Algebra Multivariate statistics
208	Direct Convex Relaxations of Sparse SVM Antoni B. Chan [removed] Nuno Vasconcelos [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:26:14 Mathematical optimization Statistical classification Operations research Model selection Support vector machines Kernel methods Semidefinite programming Quadratically constrained quadratic program Feature selection Statistics Machine learning Mathematics
209	Feature Selection in a Kernel Space Bin Cao Peking University, Beijing, China [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:25:11 Linear algebra Statistical classification Multivariate statistics Abstract algebra Signal processing Support vector machine Kernel methods Kernel principal component analysis Kernel Fisher discriminant analysis Statistics Algebra Mathematics
210	Feature Subset Selection for Learning Preferences: A Case Study Antonio Bahamonde [removed] Gustavo F. Bay´ on Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:20:39 Statistical classification Model selection Support vector machine Learning Linear algebra Cross-validation Feature selection Kernel methods Vector space Statistics Algebra Machine learning

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