Projects that are tagged with distributed.


Logo pGBRT, Parallel Gradient Boosted Regression Trees 0.9

by swtyree - September 16, 2011, 22:15:46 CET [ Project Homepage BibTeX Download ] 6649 views, 1034 downloads, 1 subscription

About: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems

Changes:

Initial Announcement on mloss.org.


Logo JMLR pebl Python Environment for Bayesian Learning 1.0.1

by abhik - March 5, 2009, 00:05:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 22316 views, 2162 downloads, 1 subscription

About: Pebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations.

Changes:

Updated version to 1.0.1


Logo dysii Dynamic Systems Library 1.4.0

by lawmurray - December 17, 2008, 17:33:41 CET [ Project Homepage BibTeX Download ] 5345 views, 1333 downloads, 0 subscriptions

About: dysii is a C++ library for distributed probabilistic inference and learning in large-scale dynamical systems. It provides methods such as the Kalman, unscented Kalman, and particle filters and [...]

Changes:

Initial Announcement on mloss.org.


Logo Disco 0.1

by tuulos - October 6, 2008, 11:14:48 CET [ Project Homepage BibTeX Download ] 6257 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 GPDT Gradient Projection Decomposition Technique 1.01

by sezaza - December 21, 2007, 20:10:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8262 views, 1464 downloads, 1 subscription

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About: This is a C++ software designed to train large-scale SVMs for binary classification. The algorithm is also implemented in parallel (**PGPDT**) for distributed memory, strictly coupled multiprocessor [...]

Changes:

Initial Announcement on mloss.org.