Statistical Uses for Distances between Permutations Anonymous Author(s) Affiliation Address email

Source URL: www.select.cs.cmu.edu

• Ordination
• Kernel methods
• Kernel principal component analysis
• Multivariate analysis
• Isomap
• Nonlinear dimensionality reduction
• Statistics
• Multivariate statistics
• Multidimensional scaling

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 7, NO. 3, JULY[removed]R

Source URL: www.is.tuebingen.mpg.de

• Imaging
• Machine learning
• Spectroscopy
• Support vector machine
• Feature selection
• Kernel methods
• Mutual information
• Reproducing kernel Hilbert space
• Kernel
• Statistics
• Statistical classification
• Multivariate statistics

Coarse-Grained Parallel Matrix-Free Solution of a Three-Dimensional Elliptic Prototype Problem Kevin P. Allen? and Matthias K. Gobbert Department of Mathematics and Statistics, University of Maryland, Baltimore County, 1

Source URL: userpages.umbc.edu

• Mathematics
• Conjugate gradient method
• Matrix
• System of linear equations
• Sparse matrix
• Parallel computing
• Kernel
• Speedup
• Matrix-free methods
• Algebra
• Linear algebra
• Numerical linear algebra

Hierarchic Bayesian Models for Kernel Learning Mark Girolami [removed] Simon Rogers [removed]

Source URL: eprints.pascal-network.org

• Regression analysis
• Support vector machine
• Relevance vector machine
• Gamma distribution
• Normal distribution
• Bayesian linear regression
• Kernel methods
• Variational Bayesian methods
• Kernel
• Statistics
• Bayesian statistics
• Statistical classification

Semi-supervised Hyperspectral Image Classification with Graphs Tatyana V. Bandos∗ , Dengyong Zhou† and Gustavo Camps-Valls∗ ∗ Dept. Enginyeria Electr`onica. Universitat de Val`encia.

Source URL: www.is.tuebingen.mpg.de

• Operator theory
• Statistical classification
• Graph theory
• Abstract algebra
• Support vector machine
• Matrix
• Hilbert space
• Kernel methods
• Graph
• Algebra
• Mathematics
• Linear algebra

Large Margin Multi-Task Metric Learning Kilian Q. Weinberger Department of Computer Science and Engineering Washington University in St. Louis St. Louis, MO 63130

Source URL: www.cse.wustl.edu

• Computational neuroscience
• Statistical classification
• Learning
• Support vector machine
• K-nearest neighbor algorithm
• Large margin nearest neighbor
• Kernel methods
• Neural network
• Pattern recognition
• Machine learning
• Statistics
• Artificial intelligence

Review of Le ture 15 • Kernel methods

Source URL: work.caltech.edu

CHATFIELD et al.: THE DEVIL IS IN THE DETAILS 1 The devil is in the details: an evaluation of recent feature encoding methods

Source URL: www.robots.ox.ac.uk

• Fisher kernel
• Code
• Histogram
• Matrix decoder
• Kernel
• Statistics
• Encoding
• Memory

Kernel Methods aren’t Dead Yet: Using Kernel Methods on Large Datasets BY EDWARD RAFF What is this about? —  Kernel Methods aka the “kernel trick”, most used in

Source URL: www.edwardraff.com

• Linear algebra
• Statistical classification
• Support vector machine
• Abstract algebra
• Functional analysis
• Kernel trick
• Kernel
• Linux kernel
• Vector space
• Algebra
• Mathematics
• Machine learning

An Avenue for High Confidence Applications in the 21st Century Timothy W. Kremann William B. Martin Frank Seaton Taylor ftimk, bradm, [removed]

Source URL: csrc.nist.gov

• Formal methods
• Formal specification
• Java virtual machine
• Kernel
• Programming language
• Specification
• Computer security
• Domain
• Abstraction
• Computing
• Software
• Cross-platform software