About: PCVM library a c++/armadillo implementation of the Probabilistic Classification Vector Machine. Changes:30.10.2015 * code has been revised in some places fixing also some errors different multiclass schemes and hdf5 file support added. Some speed ups and memory savings by better handling of intermediate objects. 27.05.2015:  Matlab binding under Windows available. Added a solution file for VS'2013 express to compile a matlab mex binding. Can not yet confirm that under windows the code is really using multiple cores (under linux it does) 29.04.2015 * added an implementation of the Nystroem based PCVM includes: Nystroem based singular value decomposition (SVD), eigenvalue decomposition (EVD) and pseudoinverse calculation (PINV) 22.04.2015 * implementation of the PCVM released

About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line. Changes:This release features the work of our 8 GSoC 2014 students [student; mentors]:
It also contains several cleanups and bugfixes: Features
Bugfixes
Cleanup and API Changes

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 writeup in written/toeblitz.pdf describing the package.

About: MSVMpack is a Multiclass Support Vector Machine (MSVM) package. It is dedicated to SVMs which can handle more than two classes without relying on decomposition methods and implements the four MSVM models from the literature: Weston and Watkins MSVM, Crammer and Singer MSVM, Lee, Lin and Wahba MSVM, and the MSVM2 of Guermeur and Monfrini. Changes:

About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semisupervised tasks. Changes:The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:
The API and ABI have undergone significant changes, many of which are due to the transition to C++11.

About: GPgrid toolkit for fast GP analysis on grid input Changes:Initial Announcement on mloss.org.

About: Fast Multidimensional GP Inference using Projected Additive Approximation Changes:Initial Announcement on mloss.org.

About: LIBSVM is an integrated software for support vector classification, (CSVC, nuSVC ), regression (epsilonSVR, nuSVR) and distribution estimation (oneclass SVM). It supports multiclass [...] Changes:Initial Announcement on mloss.org.

About: This package contains functions to estimate linear and nonlinear regression methods with Penalized Partial Least Squares. Changes:

About: Very fast implementation of the chisquared distance between histograms (or vectors with nonnegative entries). Changes:Removed bug in symmetric chisquare distance and updated python wrapper to python 2.5 compatiblity. 
About: Local alignment kernels measure the similarity between two sequences by summing up scores obtained from local alignments with gaps of the sequences. Changes:Initial Announcement on mloss.org.

About: Torch is a statistical machine learning library written in C++ at IDIAP, Changes:Initial Announcement on mloss.org.
