4 projects found that use the gpl v3 license.


Logo Toeblitz Toolkit for Fast Toeplitz Matrix Operations 1.03

by cunningham - August 13, 2014, 02:21:36 CET [ BibTeX Download ] 1977 views, 506 downloads, 2 subscriptions

About: Toeblitz is a MATLAB/Octave package for operations on positive definite Toeplitz matrices. It can solve Toeplitz systems Tx = b in O(n*log(n)) time and O(n) memory, compute matrix inverses T^(-1) (with free log determinant) in O(n^2) time and memory, compute log determinants (without inverses) in O(n^2) time and O(n) memory, and compute traces of products A*T for any matrix A, in minimal O(n^2) time and memory.

Changes:

Adding a write-up in written/toeblitz.pdf describing the package.


Logo Lua MapReduce v0.3.4

by pakozm - June 23, 2014, 11:20:59 CET [ Project Homepage BibTeX Download ] 1063 views, 228 downloads, 2 subscriptions

About: Lua-MapReduce framework implemented in Lua using luamongo driver and MongoDB as storage. It follows Iterative MapReduce for training of Machine Learning statistical models.

Changes:
  • Solved bug in reduce when num_reducers > 10
  • Added Travis CI compilation.
  • Improved efficiency of reduce merge using a heap queue.

Logo pySPACE 1.0

by krell84 - August 23, 2013, 21:00:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1536 views, 354 downloads, 1 subscription

About: --Signal Processing and Classification Environment in Python using YAML and supporting parallelization-- pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.

Changes:

First release. Initial Announcement on mloss.org.


Logo NuPIC 0.1

by rhyolight - August 21, 2013, 21:01:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1020 views, 410 downloads, 1 subscription

About: The mission of this project is to build and support a community interested in machine learning and machine intelligence based on modeling the neocortex and the principles upon which it works.

Changes:

Initial Announcement on mloss.org.