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Showing Items 451-460 of 648 on page 46 of 65: First Previous 41 42 43 44 45 46 47 48 49 50 51 Next Last

Logo r-cran-penalizedSVM 1.1

by r-cran-robot - August 2, 2010, 00:00:00 CET [ Project Homepage BibTeX Download ] 5090 views, 1046 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 Naive Bayes EM Algorithm 1.0.0

by openpr_nlpr - December 2, 2011, 05:35:09 CET [ Project Homepage BibTeX Download ] 4978 views, 1044 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 Intelligent Parameter Utilization Tool 0.4

by feldob - April 28, 2013, 18:05:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4066 views, 1039 downloads, 1 subscription

About: A descriptive and programming language independent format and API for the simplified configuration, documentation, and design of computer experiments.

Changes:

Initial Announcement on mloss.org.


Logo Semi Stochastic Gradient Descent 1.0

by konkey - July 9, 2014, 04:28:47 CET [ BibTeX BibTeX for corresponding Paper Download ] 4336 views, 1037 downloads, 1 subscription

About: Efficient implementation of Semi-Stochastic Gradient Descent algorithm (S2GD) for training logistic regression (L2-regularized).

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Initial Announcement on mloss.org.


Logo Partition Comparison 1.0

by andres - April 21, 2012, 03:26:47 CET [ Project Homepage BibTeX Download ] 3557 views, 1036 downloads, 1 subscription

About: Fast C++ implementation of the variation of information (Meila 2003) and Rand index (Rand 1971) with MATLAB mex files

Changes:

Initial Announcement on mloss.org.


Logo Multilinear Principal Component Analysis 1.2 1.2

by openpr_nlpr - April 16, 2012, 09:04:08 CET [ Project Homepage BibTeX Download ] 3778 views, 1023 downloads, 1 subscription

About: This archive contains a Matlab implementation of the Multilinear Principal Component Analysis (MPCA) algorithm and MPCA+LDA, as described in the paper Haiping Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "MPCA: Multilinear Principal Component Analysis of Tensor Objects", IEEE Transactions on Neural Networks, Vol. 19, No. 1, Page: 18-39, January 2008.

Changes:

Initial Announcement on mloss.org.


Logo Local Binary Pattern 1.0.0

by openpr_nlpr - December 2, 2011, 05:33:44 CET [ Project Homepage BibTeX Download ] 3643 views, 1023 downloads, 1 subscription

About: This is a class to calculate histogram of LBP (local binary patterns) from an input image, histograms of LBP-TOP (local binary patterns on three orthogonal planes) from an image sequence, histogram of the rotation invariant VLBP (volume local binary patterns) or uniform rotation invariant VLBP from an image sequence.

Changes:

Initial Announcement on mloss.org.


Logo SketchSort 0.0.6

by ytabei - October 11, 2010, 18:33:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5577 views, 1022 downloads, 1 subscription

About: A Sortware for All Pairs Similarity Search

Changes:

Initial Announcement on mloss.org.


Logo fastICA 0.1

by maitra - February 28, 2013, 06:30:20 CET [ Project Homepage BibTeX Download ] 4452 views, 1016 downloads, 1 subscription

About: The open-source C-package fastICA implements the fastICA algorithm of Aapo Hyvarinen et al. (URL: http://www.cs.helsinki.fi/u/ahyvarin/) to perform Independent Component Analysis (ICA) and Projection Pursuit. fastICA is released under the GNU Public License (GPL).

Changes:

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.


Showing Items 451-460 of 648 on page 46 of 65: First Previous 41 42 43 44 45 46 47 48 49 50 51 Next Last