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Logo Somoclu 1.4.1

by peterwittek - January 28, 2015, 13:19:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6403 views, 1230 downloads, 2 subscriptions

About: Somoclu is a massively parallel implementation of self-organizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Apart from a command line interface, Python, R, and MATLAB are supported.

Changes:
  • Better support for ICC.
  • Faster code when compiling with GCC.
  • Building instructions and documentation improved.
  • Bug fixes: portability for R, using native R random number generator.

About: This toolbox implements a novel visualization technique called Sectors on Sectors (SonS), and a extended version called Multidimensional Sectors on Sectors (MDSonS), for improving the interpretation of several data mining algorithms. The MDSonS method makes use of Multidimensional Scaling (MDS) to solve the main drawback of the previous method, namely, the lack of representing distances between pairs of clusters. These methods have been applied for visualizing the results of hierarchical clustering, Growing Hierarchical Self-Organizing Maps (GHSOM), classification trees and several manifolds. These methods make possible to extract all the existing relationships among centroids’ attributes at any hierarchy level.

Changes:

Initial Announcement on mloss.org.


Logo Sparse Compositional Metric Learning v1

by bellet - May 28, 2014, 09:54:10 CET [ BibTeX BibTeX for corresponding Paper Download ] 1169 views, 414 downloads, 2 subscriptions

About: Scalable learning of global, multi-task and local metrics from data

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 ] 3442 views, 824 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 Sparse PCA 1.0

by tbuehler - January 8, 2012, 19:01:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3120 views, 708 downloads, 1 subscription

About: A Matlab implementation of Sparse PCA using the inverse power method for nonlinear eigenproblems.

Changes:

Initial Announcement on mloss.org.


About: Ran He, Wei-Shi Zheng,Tieniu Tan, and Zhenan Sun. Half-quadratic based Iterative Minimization for Robust Sparse Representation. Submitted to IEEE Trans. on Pattern Analysis and Machine Intelligence.

Changes:

Initial Announcement on mloss.org.


Logo Spider 1.71

by jaseweston - November 19, 2007, 15:51:59 CET [ Project Homepage BibTeX Download ] 5725 views, 1734 downloads, 0 subscriptions

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About: The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be [...]

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 ] 5683 views, 1367 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 JMLR SSA Toolbox 1.3

by paulbuenau - January 24, 2012, 15:51:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13382 views, 4137 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 Stabilized Infinite Kernel Learning 1.0.0

by ghiasi - April 10, 2010, 08:45:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4490 views, 798 downloads, 1 subscription

About: This software is designed for learning translation invariant kernels for classification with support vector machines.

Changes:

Initial Announcement on mloss.org.


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