All entries.
Showing Items 101-120 of 676 on page 6 of 34: Previous 1 2 3 4 5 6 7 8 9 10 11 Next Last

Logo BCPy2000 17374

by jez - July 8, 2010, 22:11:24 CET [ Project Homepage BibTeX Download ] 32654 views, 6270 downloads, 0 subscriptions

About: BCPy2000 provides a platform for rapid, flexible development of experimental Brain-Computer Interface systems based on the BCI2000.org project. From the developer's point of view, the implementation [...]

Changes:

Bugfixes and tuneups, and an expanded set of (some more-, some less-documented, optional tools)


Logo FLANN, Fast Library for Approximate Nearest Neighbors 1.6.11

by mariusmuja - September 12, 2011, 22:32:29 CET [ Project Homepage BibTeX Download ] 49021 views, 6194 downloads, 0 subscriptions

About: FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms we found to work best for nearest neighbor search.

Changes:

See project page for changes.


Logo libnabo 1.0.6

by smagnenat - August 5, 2015, 12:16:40 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 32369 views, 6115 downloads, 0 subscriptions

About: libnabo is a fast K Nearset Neighbor library for low-dimensional spaces.

Changes:
  • Reset point indices of results with distances exceeding threshold (#23, #24)
  • Fine tune the find_package() capability and add uninstall target (#22)
  • Fixed compiler warning (#18)
  • Added OpenMP support (#20, #21)
  • Build type tuning (#19)
  • Fix: terminal comma in enum requires C++11
  • Fix UBSAN error calculating maxNodeCount (#16, #17)
  • Fixed tiny (yet significant) error in the Python doc strings (#15)
  • Compile static lib with PIC (#14)
  • Added configure scripts for full catkinization
  • Catkinization of libnabo (following REP136)
  • Update README.md Added Simon as the maintainer.
  • [test] use CLOCK_PROF for NetBSD build
  • Fixed CppCheck warning. Fix broken install when doxygen is not found
  • Fix cmake stylistic issue
  • Make python install respect custom CMAKE_INSTALL_PREFIX
  • Fix broken install when doxygen is not found

Logo FABIA 2.8.0

by hochreit - October 18, 2013, 10:14:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30118 views, 5965 downloads, 0 subscriptions

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
(based on 1 vote)

About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing.

Changes:

CHANGES IN VERSION 2.8.0

NEW FEATURES

o rescaling of lapla
o extractPlot does not plot sorted matrices

CHANGES IN VERSION 2.4.0

o spfabia bugfixes

CHANGES IN VERSION 2.3.1

NEW FEATURES

o Getters and setters for class Factorization

2.0.0:

  • spfabia: fabia for a sparse data matrix (in sparse matrix format) and sparse vector/matrix computations in the code to speed up computations. spfabia applications: (a) detecting >identity by descent< in next generation sequencing data with rare variants, (b) detecting >shared haplotypes< in disease studies based on next generation sequencing data with rare variants;
  • fabia for non-negative factorization (parameter: non_negative);
  • changed to C and removed dependencies to Rcpp;
  • improved update for lambda (alpha should be smaller, e.g. 0.03);
  • introduced maximal number of row elements (lL);
  • introduced cycle bL when upper bounds nL or lL are effective;
  • reduced computational complexity;
  • bug fixes: (a) update formula for lambda: tighter approximation, (b) corrected inverse of the conditional covariance matrix of z;

1.4.0:

  • New option nL: maximal number of biclusters per row element;
  • Sort biclusters according to information content;
  • Improved and extended preprocessing;
  • Update to R2.13

Logo DeeBNet, a new object oriented MATLAB toolbox for Deep Belief Networks 3.2

by keyvanrad - June 26, 2016, 16:19:55 CET [ Project Homepage BibTeX Download ] 28429 views, 5919 downloads, 0 subscriptions

About: Nowadays this is very popular to use the deep architectures in machine learning. Deep Belief Networks (DBNs) are deep architectures that use a stack of Restricted Boltzmann Machines (RBM) to create a powerful generative model using training data. DBNs have many abilities such as feature extraction and classification that are used in many applications including image processing, speech processing, text categorization, etc. This paper introduces a new object oriented toolbox with the most important abilities needed for the implementation of DBNs. According to the results of the experiments conducted on the MNIST (image), ISOLET (speech), and the 20 Newsgroups (text) datasets, it was shown that the toolbox can learn automatically a good representation of the input from unlabeled data with better discrimination between different classes. Also on all the aforementioned datasets, the obtained classification errors are comparable to those of the state of the art classifiers. In addition, the toolbox supports different sampling methods (e.g. Gibbs, CD, PCD and our new FEPCD method), different sparsity methods (quadratic, rate distortion and our new normal method), different RBM types (generative and discriminative), GPU based, etc. The toolbox is a user-friendly open source software in MATLAB and Octave and is freely available on the website.

Changes:

New in toolbox

  • Using GPU in Backpropagation
  • Revision of some demo scripts
  • Function approximation with multiple outputs
  • Feature extraction with GRBM in first layer

cardinal


Logo OpenViBE 0.8.0

by k3rl0u4rn - October 1, 2010, 16:15:08 CET [ Project Homepage BibTeX Download ] 23340 views, 5903 downloads, 0 subscriptions

Rating Whole StarWhole StarWhole StarEmpty StarEmpty Star
(based on 1 vote)

About: OpenViBE is an opensource platform that enables to design, test and use Brain-Computer Interfaces (BCI). Broadly speaking, OpenViBE can be used in many real-time Neuroscience applications [...]

Changes:

New release 0.8.0.


Logo UniverSVM 1.22

by fabee - October 16, 2012, 11:24:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37815 views, 5902 downloads, 0 subscriptions

About: The UniverSVM is a SVM implementation written in C/C++. Its functionality comprises large scale transduction via CCCP optimization, sparse solutions via CCCP optimization and data-dependent [...]

Changes:

Minor changes: fix bug on set_alphas_b0 function (thanks to Ferdinand Kaiser - ferdinand.kaiser@tut.fi)


Logo r-cran-rattle 2.6.26

by r-cran-robot - March 16, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 25835 views, 5860 downloads, 0 subscriptions

About: Graphical user interface for data mining in R

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:07.700426


Logo Orange 2.6

by janez - February 14, 2013, 18:15:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30486 views, 5833 downloads, 0 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 1 vote)

About: Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

Changes:

The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL.

Changed the BibTeX reference to the paper recently published in JMLR MLOSS.


Logo r-cran-GAMBoost 1.2-2

by r-cran-robot - April 1, 2013, 00:00:04 CET [ Project Homepage BibTeX Download ] 28309 views, 5773 downloads, 0 subscriptions

About: Generalized linear and additive models by likelihood based boosting

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:04.893311


Logo KeplerWeka 20101008

by fracpete - October 9, 2010, 05:27:13 CET [ Project Homepage BibTeX Download ] 20520 views, 5672 downloads, 0 subscriptions

About: KeplerWeka represents the integration of all the functionality of the WEKA Machine Learning Workbench into the open-source scientific workflow Kepler. Among them are classification, [...]

Changes:
  • Now compatible with Kepler 2.0
  • New version of WEKA included (patched 3.7.2 release), WEKA's new package manager works in conjunction with Kepler
  • Renamed actor Count to ConditionalTee, introduced new Count actor
  • Removed actors OutputLogger, MultiSync, TwinSync

Logo figtree 0.9.2

by vmorariu - January 17, 2009, 00:13:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9904 views, 5577 downloads, 0 subscriptions

About: A library for fast computation of Gauss transforms in multiple dimensions, using the Improved Fast Gauss Transform and a tree data structure. This library is useful for efficient Kernel Density [...]

Changes:

Initial Announcement on mloss.org.


Logo A Local and Parallel Computation Toolbox for Gaussian Process Regression 1.0

by cwpark - March 19, 2012, 17:21:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18487 views, 5572 downloads, 0 subscriptions

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 PREA Personalized Recommendation Algorithms Toolkit 1.1

by srcw - September 1, 2012, 22:53:37 CET [ Project Homepage BibTeX Download ] 22054 views, 5560 downloads, 0 subscriptions

About: An open source Java software providing collaborative filtering algorithms.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-VR 7.2-49

by r-cran-robot - September 25, 2009, 00:00:00 CET [ Project Homepage BibTeX Download ] 23152 views, 5553 downloads, 0 subscriptions

About: VR

Changes:

Fetched by r-cran-robot on 2009-10-03 07:16:05.643423


Logo 1SpectralClustering 1.2

by tbuehler - May 1, 2018, 19:26:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27778 views, 5539 downloads, 0 subscriptions

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

Changes:
  • improved optimization of ncut and rcut criterion
  • optimized eigenvector initialization
  • changed default values for number of runs
  • several internal optimizations
  • made console output more informative

Logo Aika 0.17

by molzberger - May 14, 2018, 15:42:00 CET [ Project Homepage BibTeX Download ] 21331 views, 5527 downloads, 0 subscriptions

About: Aika is an open source text mining engine. It can automatically extract and annotate semantic information in text. In case this information is ambiguous, Aika will generate several hypothetical interpretations about the meaning of this text and retrieve the most likely one.

Changes:

Aika Version 0.17 2018-05-14

  • Introduction of synapse relations. Previously the relation between synapses was implicitly modeled through word positions (RIDs). Now it is possible to explicitly model relations like: The end position of input activation 1 equals to the begin position of input activation 2. Two types of relations are currently supported, range relations and instance relations. Range relations compare the input activation range of a given synapse with that of the linked synapse. Instance relations also compare the input activations of two synapses, but instead of the ranges the dependency relations of these activations are compared.
  • Removed the norm term from the interpretation objective function.
  • Introduction of an optional distance function to synapses. It allows to model a weakening signal depending on the distance of the activation ranges.
  • Example implementation of a context free grammar.
  • Example implementation for co-reference resolution.
  • Work on an syllable identification experiment based on the meta network implementation.

Aika Version 0.15 2018-03-16

  • Simplified interpretation handling by removing the InterpretationNode class and moving the remaining logic to the Activation class.
  • Moved the activation linking and activation selection code to separate classes.
  • Ongoing work on the training algorithms.

Logo JMLR FastInf 1.0

by arielj - June 4, 2010, 14:04:37 CET [ Project Homepage BibTeX Download ] 16100 views, 5509 downloads, 0 subscriptions

About: The library is focused on implementation of propagation based approximate inference methods. Also implemented are a clique tree based exact inference, Gibbs sampling, and the mean field algorithm.

Changes:

Initial Announcement on mloss.org.


Logo The Infinite Hidden Markov Model 0.5

by jvangael - July 21, 2010, 23:41:24 CET [ BibTeX BibTeX for corresponding Paper Download ] 31833 views, 5478 downloads, 0 subscriptions

About: An implementation of the infinite hidden Markov model.

Changes:

Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.


Logo JProGraM 13.2

by ninofreno - February 13, 2013, 20:29:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 28719 views, 5463 downloads, 0 subscriptions

About: JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random graphs/fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.

Changes:

JProGraM 13.2 -- CHANGE LOG

Release date: February 13, 2012

New features: -- Support for Fiedler random graphs/random field models for large-scale networks (ninofreno.graph.fiedler package); -- Various bugfixes and enhancements (especially in the ninofreno.graph and ninofreno.math package).


Showing Items 101-120 of 676 on page 6 of 34: Previous 1 2 3 4 5 6 7 8 9 10 11 Next Last