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Logo A Parallel LDA Learning Toolbox 1.0

by yanjianfeng - January 24, 2014, 11:48:07 CET [ BibTeX Download ] 954 views, 313 downloads, 1 subscription

About: We introduces PLL, a parallel LDA learning toolbox for big topic modeling.

Changes:

Fix some compiling errors.


Logo Linear Discriminant Function Classifier 1.0.0

by openpr_nlpr - December 2, 2011, 05:27:27 CET [ Project Homepage BibTeX Download ] 1167 views, 309 downloads, 1 subscription

About: This program is a C++ implementation of Linear Discriminant Function Classifier. Discriminant functions such as perceptron criterion, cross entropy (CE) criterion, and least mean square (LMS) criterion (all for multi-class classification problems) are supported in it. The program uses a sparse-data structure to represent the feature vector to seek higher computational speed. Some other techniques such as online updating, weights averaging, gaussian prior regularization are also supported.

Changes:

Initial Announcement on mloss.org.


Logo GPgrid toolkit for fast GP analysis on grid input 0.1

by ejg20 - September 16, 2013, 18:01:16 CET [ BibTeX Download ] 882 views, 304 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.


Logo Probabilistic Latent Semantic Indexing 1.0.0

by openpr_nlpr - December 2, 2011, 04:42:02 CET [ Project Homepage BibTeX Download ] 1207 views, 300 downloads, 1 subscription

About: Hofmann, T. 1999. Probabilistic latent semantic indexing. In Proceedings of the 22nd ACM-SIGIR International Conference on Research and Development in Information Retrieval (Berkeley,Calif.), ACM, New York, 50–57.

Changes:

Initial Announcement on mloss.org.


Logo Differential Dependency Network cabig cytoscape plugin 1.0

by cbil - October 27, 2013, 17:31:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1326 views, 290 downloads, 1 subscription

About: DDN learns and visualize differential dependency networks from condition-specific data.

Changes:

Initial Announcement on mloss.org.


Logo JMLR BudgetedSVM v1.1

by nemanja - February 12, 2014, 20:53:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1424 views, 284 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 Java deep neural networks with GPU 0.2.0-alpha

by hok - May 10, 2014, 14:22:30 CET [ Project Homepage BibTeX Download ] 1147 views, 283 downloads, 2 subscriptions

About: GPU-accelerated java deep neural networks

Changes:

Initial Announcement on mloss.org.


About: Robust sparse representation has shown significant potential in solving challenging problems in computer vision such as biometrics and visual surveillance. Although several robust sparse models have been proposed and promising results have been obtained, they are either for error correction or for error detection, and learning a general framework that systematically unifies these two aspects and explore their relation is still an open problem. In this paper, we develop a half-quadratic (HQ) framework to solve the robust sparse representation problem. By defining different kinds of half-quadratic functions, the proposed HQ framework is applicable to performing both error correction and error detection. More specifically, by using the additive form of HQ, we propose an L1-regularized error correction method by iteratively recovering corrupted data from errors incurred by noises and outliers; by using the multiplicative form of HQ, we propose an L1-regularized error detection method by learning from uncorrupted data iteratively. We also show that the L1-regularization solved by soft-thresholding function has a dual relationship to Huber M-estimator, which theoretically guarantees the performance of robust sparse representation in terms of M-estimation. Experiments on robust face recognition under severe occlusion and corruption validate our framework and findings.

Changes:

Initial Announcement on mloss.org.


Logo NearOED 1.0

by gabobert - July 11, 2013, 16:54:12 CET [ Project Homepage BibTeX Download ] 1043 views, 275 downloads, 1 subscription

About: The toolbox from the paper Near-optimal Experimental Design for Model Selection in Systems Biology (Busetto et al. 2013, submitted) implemented in MATLAB.

Changes:

Initial Announcement on mloss.org.


Showing Items 481-490 of 541 on page 49 of 55: First Previous 44 45 46 47 48 49 50 51 52 53 54 Next Last