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Logo Disco 0.1

by tuulos - October 6, 2008, 11:14:48 CET [ Project Homepage BibTeX Download ] 6260 views, 1239 downloads, 1 subscription

About: Disco is an open-source implementation of the [Map-Reduce framework](http://en.wikipedia.org/wiki/MapReduce) for distributed computing. As the original framework, Disco supports parallel [...]

Changes:

Initial Announcement on mloss.org.


Logo SnOB beta

by risi - October 5, 2008, 21:39:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3907 views, 841 downloads, 1 subscription

About: SnOB is a C++ library implementing fast Fourier transforms on the symmetric group (group of permutations). Such Fourier transforms are used by some ranking and identity management algorithms, as [...]

Changes:

Initial Announcement on mloss.org.


About: GMRFLib is a library in C for fast and exact simulation of Gaussian Markov Random Fields (GMRF) on graphs.unconditional simulation of a GMRF, conditional simulation from a GMRF

Changes:

Initial Announcement on mloss.org.


Logo Spike train feature extraction by Bayesian binning 0.1

by dendres - September 24, 2008, 16:19:14 CET [ BibTeX BibTeX for corresponding Paper Download ] 5459 views, 1304 downloads, 0 comments, 1 subscription

About: *binsdfc* is a command line implementation of the algorithm described in [Endres,Oram,Schindelin,Foldiak:*Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms*, [...]

Changes:

Changed build system from automake to cmake. Moved download page to www.compsens.uni-tuebingen.de


Logo aureservoir 0.1

by grh - September 12, 2008, 19:02:26 CET [ Project Homepage BibTeX Download ] 4424 views, 1375 downloads, 1 subscription

About: Efficient C++ library for analog reservoir computing neural networks (Echo State Networks).

Changes:

Initial Announcement on mloss.org.


Logo aiParts 0.9.0

by bmarshall - September 8, 2008, 02:56:43 CET [ Project Homepage BibTeX Download ] 4085 views, 1176 downloads, 0 comments, 1 subscription

About: aiParts implements the High-Hope technique - options have models of emotions which affect and are affected by repeated attempts to solve a multi-decision problem. C++ classes for AI development.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-rdetools 1.0

by r-cran-robot - September 3, 2008, 00:00:00 CET [ Project Homepage BibTeX Download ] 3065 views, 777 downloads, 1 subscription

About: Relevant Dimension Estimation (RDE) in Feature Spaces: The package provides functions for estimating the relevant dimension of a data set in feature spaces, applications to model selection, [...]

Changes:

Initial Announcement on mloss.org.


Logo NetKit 1.0.3

by sofmac - August 24, 2008, 07:45:10 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4170 views, 1111 downloads, 0 comments, 1 subscription

About: NetKit is an open-source Network Learning toolkit for statistical relational learning. Its architecture is extremely modular, making it easy to combine different learning algorithms.

Changes:

Initial Announcement on mloss.org.


Logo Ngram Statistics Package 1.09

by tpederse - August 12, 2008, 18:21:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5720 views, 1243 downloads, 0 comments, 1 subscription

About: The Ngram Statistics Package is a suite of Perl modules that identifies significant multi-word units (collocations) in written text using many different tests of association. NSP allows a user to [...]

Changes:

Initial Announcement on mloss.org.


Logo WordNet Similarity 2.05

by tpederse - August 12, 2008, 16:42:50 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5496 views, 1362 downloads, 2 subscriptions

About: This is a Perl module that implements a variety of semantic similarity and relatedness measures based on information found in the lexical database WordNet. In particular, it supports the measures of [...]

Changes:

Initial Announcement on mloss.org.


Showing Items 491-500 of 539 on page 50 of 54: First Previous 45 46 47 48 49 50 51 52 53 54 Next