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Logo pboost 1.0

by nowozin - November 13, 2007, 08:48:28 CET [ Project Homepage BibTeX Download ] 4354 views, 1117 downloads, 0 subscriptions

About: The pboost toolbox is a set of command line programs and a Matlab wrapper for mining frequent subsequences and sequence classification. For our purposes, a sequence is defined an ordered sequence of [...]

Changes:

Initial Announcement on mloss.org.


About: You should never compute, maintain, or update the inverse of a symmetric positive definite matrix if you do not have to. Computing the inverse or manipulating it is inherently instable. You can [...]

Changes:

Initial Announcement on mloss.org.


Logo PyStruct 0.2

by t3kcit - July 9, 2014, 09:29:23 CET [ Project Homepage BibTeX Download ] 4296 views, 1099 downloads, 1 subscription

About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the well-known SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation.

Changes:

Initial Announcement on mloss.org.


Logo COIN OR 1.2

by sonne - July 13, 2009, 10:51:10 CET [ Project Homepage BibTeX Download ] 4263 views, 1318 downloads, 1 subscription

About: The Computational Infrastructure for Operations Research (COIN-OR) project is an initiative to spur the development of open-source software for the operations research community.

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Initial Announcement on mloss.org.


About: We study the problem of robust feature extraction based on L21 regularized correntropy in both theoretical and algorithmic manner. In theoretical part, we point out that an L21-norm minimization can be justified from the viewpoint of half-quadratic (HQ) optimization, which facilitates convergence study and algorithmic development. In particular, a general formulation is accordingly proposed to unify L1-norm and L21-norm minimization within a common framework. In algorithmic part, we propose an L21 regularized correntropy algorithm to extract informative features meanwhile to remove outliers from training data. A new alternate minimization algorithm is also developed to optimize the non-convex correntropy objective. In terms of face recognition, we apply the proposed method to obtain an appearance-based model, called Sparse-Fisherfaces. Extensive experiments show that our method can select robust and sparse features, and outperforms several state-of-the-art subspace methods on largescale and open face recognition datasets.

Changes:

Initial Announcement on mloss.org.


About: Fast Multidimensional GP Inference using Projected Additive Approximation

Changes:

Initial Announcement on mloss.org.


Logo r-cran-penalizedSVM 1.1

by r-cran-robot - August 2, 2010, 00:00:00 CET [ Project Homepage BibTeX Download ] 4195 views, 894 downloads, 0 subscriptions

About: Feature Selection SVM using penalty functions

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Fetched by r-cran-robot on 2013-04-01 00:00:07.509844


Logo JMLR BudgetedSVM v1.1

by nemanja - February 12, 2014, 20:53:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4160 views, 789 downloads, 1 subscription

About: BudgetedSVM is an open-source C++ toolbox for scalable non-linear classification. The toolbox can be seen as a missing link between LibLinear and LibSVM, combining the efficiency of linear with the accuracy of kernel SVM. We provide an Application Programming Interface for efficient training and testing of non-linear classifiers, supported by data structures designed for handling data which cannot fit in memory. We also provide command-line and Matlab interfaces, providing users with an efficient, easy-to-use tool for large-scale non-linear classification.

Changes:

Changed license from LGPL v3 to Modified BSD.


Logo Naive Bayes EM Algorithm 1.0.0

by openpr_nlpr - December 2, 2011, 05:35:09 CET [ Project Homepage BibTeX Download ] 4148 views, 895 downloads, 1 subscription

About: OpenPR-NBEM is an C++ implementation of Naive Bayes Classifier, which is a well-known generative classification algorithm for the application such as text classification. The Naive Bayes algorithm requires the probabilistic distribution to be discrete. OpenPR-NBEM uses the multinomial event model for representation. The maximum likelihood estimate is used for supervised learning, and the expectation-maximization estimate is used for semi-supervised and un-supervised learning.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-grpreg 2.3-0

by r-cran-robot - February 10, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 4147 views, 983 downloads, 0 subscriptions

About: Regularization paths for regression models with grouped covariates

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Fetched by r-cran-robot on 2013-04-01 00:00:05.489694


Showing Items 411-420 of 624 on page 42 of 63: First Previous 37 38 39 40 41 42 43 44 45 46 47 Next Last