Projects that are tagged with kernel.


Logo JMLR MSVMpack 1.5

by lauerfab - July 3, 2014, 16:02:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10266 views, 3568 downloads, 2 subscriptions

About: MSVMpack is a Multi-class Support Vector Machine (M-SVM) package. It is dedicated to SVMs which can handle more than two classes without relying on decomposition methods and implements the four M-SVM models from the literature: Weston and Watkins M-SVM, Crammer and Singer M-SVM, Lee, Lin and Wahba M-SVM, and the M-SVM2 of Guermeur and Monfrini.

Changes:
  • Windows binaries are now included (by Emmanuel Didiot)
  • MSVMpack can now be compiled on Windows (by Emmanuel Didiot)
  • Fixed polynomial kernel
  • Minor bug fixes

Logo JMLR EnsembleSVM 2.0

by claesenm - March 31, 2014, 08:06:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4118 views, 1479 downloads, 2 subscriptions

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 semi-supervised 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:

  1. Support for multithreading in training and prediction with ensemble models. Since both of these are embarassingly parallel, this has induced a significant speedup (3-fold on quad-core).
  2. Extensive programming framework for aggregation of base model predictions which allows highly efficient prototyping of new aggregation approaches. Additionally we provide several predefined strategies, including (weighted) majority voting, logistic regression and nonlinear SVMs of your choice -- be sure to check out the esvm-edit tool! The provided framework also allows you to efficiently program your own, novel aggregation schemes.
  3. Full code transition to C++11, the latest C++ standard, which enabled various performance improvements. The new release requires moderately recent compilers, such as gcc 4.7.2+ or clang 3.2+.
  4. Generic implementations of convenient facilities have been added, such as thread pools, deserialization factories and more.

The API and ABI have undergone significant changes, many of which are due to the transition to C++11.


Logo JMLR SHOGUN 3.2.0

by sonne - February 17, 2014, 20:31:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 81611 views, 11250 downloads, 5 subscriptions

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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 is mostly a bugfix release:

Features

  • Fully support python3 now
  • Add mini-batch k-means [Parijat Mazumdar]
  • Add k-means++ [Parijat Mazumdar]
  • Add sub-sequence string kernel [lambday]

Bugfixes

  • Compile fixes for upcoming swig3.0
  • Speedup for gaussian process' apply()
  • Improve unit / integration test checks
  • libbmrm uninitialized memory reads
  • libocas uninitialized memory reads
  • Octave 3.8 compile fixes [Orion Poplawski]
  • Fix java modular compile error [Bjoern Esser]

Logo GPgrid toolkit for fast GP analysis on grid input 0.1

by ejg20 - September 16, 2013, 18:01:16 CET [ BibTeX Download ] 647 views, 239 downloads, 1 subscription

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: 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 tar directly instead of via link


Logo LIBSVM 2.9

by cjlin - February 27, 2010, 01:09:23 CET [ Project Homepage BibTeX Download ] 10300 views, 2099 downloads, 1 subscription

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About: LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC ), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class [...]

Changes:

Initial Announcement on mloss.org.


Logo Penalized Partial Least Squares Regression 1.03

by nkraemer - May 5, 2009, 19:53:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8787 views, 1292 downloads, 0 subscriptions

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

Changes:
  • fixed several bugs
  • drastic speed-up of computation time

Logo chi2 kernel 1.5

by gruel - February 15, 2009, 22:32:21 CET [ BibTeX Download ] 8552 views, 1904 downloads, 1 subscription

About: Very fast implementation of the chi-squared distance between histograms (or vectors with non-negative entries).

Changes:

Removed bug in symmetric chi-square distance and updated python wrapper to python 2.5 compatiblity.


Logo Local Alignment Kernels 0.3.2

by hiroto - December 1, 2007, 00:10:23 CET [ Project Homepage BibTeX Download ] 5233 views, 1226 downloads, 0 subscriptions

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.


Logo Torch 3

by bengio - November 13, 2007, 01:38:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5499 views, 1445 downloads, 1 subscription

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About: Torch is a statistical machine learning library written in C++ at IDIAP,

Changes:

Initial Announcement on mloss.org.