zikai1/DSPKM

This is the page for the book Digital Signal Processing with Kernel Methods.

DSPKM

This is the page for the book Digital Signal Processing with Kernel Methods.

Links to toolboxes, code and software

Chapter 03

• Image denosing and coding: ViStaCoRe: http://isp.uv.es/soft_imvideo.html

Chapter 04

• Interpolation: simpleInterp: http://www.tsc.urjc.es/jlrojo

Chapter 06

• Kernel gamma and kernel ARMA: http://isp.uv.es/soft_regression.html
• KARMA: Kernel AutoRegressive Moving Average with SVM: http://isp.uv.es/code/regression/karma.zip
• ARX-RVM: Autorregressive eXogenous Relevance Vector Machine: http://isp.uv.es/code/regression/karma_rvm.zip

Chapter 08

• Simple Regression Toolbox, simpleR: http://isp.uv.es/soft_regression.html

• MSVR: Multioutput Support Vector Regression: http://isp.uv.es/code/regression/msvr-2-1.zip

• Semisupervised SVR: http://isp.uv.es/soft_regression.html, http://isp.uv.es/code/regression/demoSemiSVR.zip

• e-Huber: Epsilon-Huber Support Vector Regression: http://isp.uv.es/code/regression/svr_e_huber.zip

• KSNR: Kernel Signal to Noise Ratio: http://isp.uv.es/code/regression/ksnr.zip

• WGPR: Warped GPR: http://www.tsc.uc3m.es/~miguel/downloads.php

• VHGPR: Variational Heteroscedastic GPR: http://www.tsc.uc3m.es/~miguel/downloads.php

• Relevance vector machine (RVM): Two available toolboxes are suggested:

  1. Original: http://www.miketipping.com/sparsebayes.htm
  2. Multivariate RVM (MRVM) implementation by Arasanathan Thayananthan (at315@cam.ac.uk)(c) Copyright University of Cambridge. Please cite the original implementation when appropriate: Multivariate Relevance Vector Machines for Tracking, Arasanathan Thayananthan et al. (University of Cambridge). In Proc. 9th European Conference on Computer Vision 2006.
  • NOTE: Wrapper functions to the later MRVM are included in simpleR: http://isp.uv.es/soft_regression.html

• SVR: The original source code of libsvm can be obtained from http://www.csie.ntu.edu.tw/~cjlin/libsvm/. The same toolbox with some modifications an additions at http://www.uv.es/jordi/soft.htm

• KARMA: Kernel AutoRegressive Moving Average with SVM: http://isp.uv.es/code/regression/karma.zip

• ARX-RVM: Autorregressive eXogenous Relevance Vector Machine: http://isp.uv.es/code/regression/karma_rvm.zip

Chapter 09

• Kernel Adaptive Filtering Toolbox (KAFBOX): https://github.com/steven2358/kafbox/

Chapter 10

• SVM:
  • libSVM can be obtained from http://www.csie.ntu.edu.tw/~cjlin/libsvm/
  • Alternative toolbox with some additions at http://www.uv.es/jordi/soft.htm
  • General-purpose toolboxes for classification: http://isp.uv.es/soft_classification.html
  • LS-SVM: http://www.esat.kuleuven.be/sista/lssvmlab/
  • KFD: https://github.com/lawrennd/nkfd
• Laplacian SVM:
  • http://www.dii.unisi.it/~melacci/lapsvmp/
  • http://manifold.cs.uchicago.edu/manifold_regularization/software.html
• Transductive SVM: http://svmlight.joachims.org/
• Semisupervised learning: An interesting collection of semisupervised learning software is available at http://pages.cs.wisc.edu/~jerryzhu/ssl/software.html
• Structured-output SVM:
  • Original SVM$ struct toolbox: http://svmlight.joachims.org/
  • Some useful wrapper functions at http://www.robots.ox.ac.uk/~vedaldi/svmstruct.html
• Large Margin Filtering: http://remi.flamary.com/soft/soft-filtersvm.html
• Active Learning: Active Learning MATLAB(tm) Toolbox at https://github.com/IPL-UV/altoolbox/

Chapter 11

• Density estimation: MATLAB KDE toolbox: http://www.ics.uci.edu/~ihler/code/kde.html
• One-Class SVM:
  • libSVM can be obtained from http://www.csie.ntu.edu.tw/~cjlin/libsvm/
  • Alternative toolbox with some additions at http://www.uv.es/jordi/soft.htm
• One-Class Support Measure Machine, OCSMM: http://webdav.tuebingen.mpg.de/smm/
• Lots of one-class methods, not necessarily kernels:
  • dd_tools: http://prlab.tudelft.nl/david-tax/dd_tools.html

Chapter 12

• SIMFEAT, A simple Feature Extraction Toolbox: http://isp.uv.es/soft_feature.html
• Kernel dependence estimates:
  • A set of MATLAB toolbox for HSIC can be found at http://www.gatsby.ucl.ac.uk/~gretton/indepTestFiles/indep.htm
  • Information Theoretical Estimators (ITE) Toolbox: https://bitbucket.org/szzoli/ite/
  • For HSIC-based feature extraction methods, use SIMFEAT toolbox and gKDR software at http://www.ism.ac.jp/~fukumizu/software.html
  • FastICA: https://research.ics.aalto.fi/ica/fastica/
  • KICA: http://www.di.ens.fr/~fbach/kernel-ica/, http://people.kyb.tuebingen.mpg.de/arthur/fastkica.htm
• Domain adaptation:
  • Kernel mean matching (KMM): http://www.cs.cmu.edu/~arthurg/covariateShiftFiles/covariateShiftSoftware.html
  • Transfer component analysis, TCA: https://github.com/viggin/domain-adaptation-toolbox
  • KEMA, kernel manifold alignment: https://github.com/dtuia/KEMA/