Projects supporting the matlab data format.
Showing Items 41-60 of 72 on page 3 of 4: Previous 1 2 3 4 Next

Logo Uncorrelated Multilinear Principal Component Analysis 1.0

by hplu - June 18, 2012, 17:23:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4299 views, 917 downloads, 1 subscription

About: A Matlab implementation of Uncorrelated Multilinear PCA (UMPCA) for dimensionality reduction of tensor data via tensor-to-vector projection

Changes:

Initial Announcement on mloss.org.


About: The package provides a Lagrangian approach to the posterior regularization of given linear mappings. This is important in two cases, (a) when systems are under-determined and (b) when the external model for calculating the mapping is invariant to properties such as scaling. The software may be applied in cases when the external model does not provide its own regularization strategy. In addition, the package allows to rank attributes according to their distortion potential to a given linear mapping.

Changes:

Version 1.1 (May 23, 2012) memory and time optimizations distderivrel.m now supports assessing the relevance of attribute pairs

Version 1.0 (Nov 9, 2011) * Initial Announcement on mloss.org.


Logo Output Kernel Learning 2.0

by posaune - March 22, 2012, 11:34:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7470 views, 1261 downloads, 1 subscription

About: A Matlab script for learning vector-valued functions and kernels on the output space.

Changes:

Added code for learning low-rank output kernels.


Logo GP RTSS 1.0

by marc - March 21, 2012, 08:43:52 CET [ BibTeX BibTeX for corresponding Paper Download ] 3957 views, 1172 downloads, 1 subscription

About: Gaussian process RTS smoothing (forward-backward smoothing) based on moment matching.

Changes:

Initial Announcement on mloss.org.


About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software.

Changes:

Initial Announcement on mloss.org.


Logo Sparse MultiTask Learning Toolbox 1.2

by rflamary - March 18, 2012, 11:31:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5993 views, 1307 downloads, 1 subscription

About: This package is a set of Matlab scripts that implements the algorithms described in the submitted paper: "Lp-Lq Sparse Linear and Sparse Multiple Kernel MultiTask Learning".

Changes:

Initial Announcement on mloss.org.


Logo multi assignment clustering of Boolean data 2.001

by mafrank - March 3, 2012, 09:04:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8561 views, 1261 downloads, 1 subscription

About: Implementation of the multi-assignment clustering method for Boolean vectors.

Changes:

new bib added


Logo Large margin filtering 0.9

by rflamary - February 18, 2012, 15:50:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4816 views, 1211 downloads, 1 subscription

About: Matlab SVM toolbox for learning large margin filters in signal or images.

Changes:

Initial Announcement on mloss.org.


Logo JMLR SSA Toolbox 1.3

by paulbuenau - January 24, 2012, 15:51:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21134 views, 6331 downloads, 1 subscription

About: The SSA Toolbox is an efficient, platform-independent, standalone implementation of the Stationary Subspace Analysis algorithm with a friendly graphical user interface and a bridge to Matlab. Stationary Subspace Analysis (SSA) is a general purpose algorithm for the explorative analysis of non-stationary data, i.e. data whose statistical properties change over time. SSA helps to detect, investigate and visualize temporal changes in complex high-dimensional data sets.

Changes:
  • Various bugfixes.

Logo GraphLab v1-1908

by dannybickson - November 22, 2011, 12:50:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7944 views, 1280 downloads, 1 subscription

About: Multicore/distributed large scale machine learning framework.

Changes:

Update version.


Logo Denoising TOF 3D images using confidence measures 1

by mafrank - August 17, 2011, 16:59:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4875 views, 1004 downloads, 1 subscription

About: Denoising images via normalized convolution

Changes:

Initial Announcement on mloss.org.


About: Multi-class vector classification based on cost function-driven learning vector quantization , minimizing misclassification.

Changes:

Initial Announcement on mloss.org.


Logo BRML toolbox 070711

by DavidBarber - July 17, 2011, 19:30:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 64459 views, 4731 downloads, 1 subscription

About: Bayesian Reasoning and Machine Learning toolbox

Changes:

Fixed some small bugs and updated some demos.


Logo Correlative Matrix Mapping, CMM 1.1

by emstrick - July 5, 2011, 15:15:21 CET [ BibTeX BibTeX for corresponding Paper Download ] 6921 views, 1582 downloads, 1 subscription

About: Correlative Matrix Mapping (CMM) provides a supervised linear data mapping into a Euclidean subspace of given dimension. Applications include denoising, visualization, label-specific data preprocessing, and assessment of data attribute pairs relevant for the supervised mapping. Solving auto-association problems yields linear multidimensional scaling, similar to PCA, but usually with more faithful low-dimensional mappings.

Changes:

Tue Jul 5 14:40:03 CEST 2011 - Bugfixes and cleanups

  • single precision data affected pinv(). Now fairer using double precision.
  • early stopping did not work properly; now fixed
  • Hessian update mode globally controlled via hessmode, 'lbfgs' / 'bfgs'
  • distmat.m corrected for rounding problems and extended to distmat(X,Y)
  • replaced files: corv.m + corvgrad.m -> corvg.m
  • removed unused files: corrmat.m, splitdata.m, traforankapply.m

Logo 1SpectralClustering 1.1

by tbuehler - June 27, 2011, 10:45:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11062 views, 2169 downloads, 1 subscription

About: A fast and scalable graph-based clustering algorithm based on the eigenvectors of the nonlinear 1-Laplacian.

Changes:
  • fixed bug occuring when input graph is disconnected
  • reduced memory usage when input graph has large number of disconnected components
  • more user-friendly usage of main method OneSpectralClustering
  • faster computation of eigenvector initialization + now thresholded according to multicut-criterion
  • several internal optimizations

About: Matlab implementation of variational gaussian approximate inference for Bayesian Generalized Linear Models.

Changes:

Code restructure and bug fix.


Logo mldata.org svn-r1070-Apr-2011

by sonne - April 8, 2011, 10:15:49 CET [ Project Homepage BibTeX Download ] 5519 views, 1277 downloads, 1 subscription

About: The source code of the mldata.org site - a community portal for machine learning data sets.

Changes:

Initial Announcement on mloss.org.


Logo mldata-utils 0.5.0

by sonne - April 8, 2011, 10:02:44 CET [ Project Homepage BibTeX Download ] 31951 views, 6925 downloads, 1 subscription

About: Tools to convert datasets from various formats to various formats, performance measures and API functions to communicate with mldata.org

Changes:
  • Change task file format, such that data splits can have a variable number items and put into up to 256 categories of training/validation/test/not used/...
  • Various bugfixes.

Logo JMLR Surrogate Modeling Toolbox 7.0.2

by dgorissen - September 4, 2010, 07:48:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 17838 views, 4846 downloads, 1 subscription

About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive.

Changes:

Incremental update, fixing some cosmetic issues, coincides with JMLR publication.


About: The gmm toolbox contains code for density estimation using mixtures of Gaussians: Starting from simple kernel density estimation with spherical and diagonal Gaussian kernels over manifold Parzen window until mixtures of penalised full Gaussians with only a few components. The toolbox covers many Gaussian mixture model parametrisations from the recent literature. Most prominently, the package contains code to use the Gaussian Process Latent Variable Model for density estimation. Most of the code is written in Matlab 7.x including some MEX files.

Changes:

Initial Announcement on mloss.org


Showing Items 41-60 of 72 on page 3 of 4: Previous 1 2 3 4 Next