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Logo bandicoot 0.4

by yvesalexandre - November 20, 2015, 17:08:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4465 views, 927 downloads, 0 subscriptions

About: An open-source Python toolbox to analyze mobile phone metadata.

Changes:

Initial Announcement on mloss.org.


Logo Agglomerative MeanShift Clustering 1.0.0

by openpr_nlpr - December 2, 2011, 04:38:13 CET [ Project Homepage BibTeX Download ] 4459 views, 1181 downloads, 0 subscriptions

About: Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets. For the purpose of algorithm speedup, an agglomerative MS clustering method called Agglo-MS was developed, along with its mode-seeking ability and convergence property analysis. The method is built upon an iterative query set compression mechanism which is motivated by the quadratic bounding optimization nature of MS. The whole framework can be efficiently implemented in linear running time complexity.

Changes:

Initial Announcement on mloss.org.


Logo AIDE 0.2

by khalili - January 3, 2014, 18:01:06 CET [ Project Homepage BibTeX Download ] 4457 views, 1259 downloads, 0 subscriptions

About: AIDE (Automata Identification Engine) is a free open source tool for automata inference algorithms developed in C# .Net.

Changes:

Initial Announcement on mloss.org.


Logo Loom 0.2.10

by fritzo - March 19, 2015, 19:22:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4404 views, 1065 downloads, 0 subscriptions

About: A streaming inference and query engine for the Cross-Categorization model of tabular data.

Changes:

Initial Announcement on mloss.org.


Logo Histogram of Oriented Gradient 1.0

by openpr_nlpr - February 10, 2015, 08:27:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4404 views, 881 downloads, 0 subscriptions

About: This is an exact implementation of Histogram of Oriented Gradient as mentioned in the paper by Dalal.

Changes:

Initial Announcement on mloss.org.


Logo BOLeRo 1.0.0

by afabisch - February 11, 2018, 19:44:41 CET [ Project Homepage BibTeX Download ] 4359 views, 1301 downloads, 0 subscriptions

About: Behavior Optimization and Learning for Robots

Changes:

https://github.com/rock-learning/bolero/releases/tag/v1.0.0


Logo Databases for DMNS source codes 1.0

by openpr_nlpr - May 15, 2018, 07:56:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4357 views, 921 downloads, 0 subscriptions

About: In DMNS source, five databases are used in slover.cpp and data_veh_layer.cpp, these images and databases are included in this file, except munich database.

Changes:

Initial Announcement on mloss.org.


Logo Baycomp 1.0

by janez - March 7, 2018, 01:37:12 CET [ Project Homepage BibTeX Download ] 4350 views, 1408 downloads, 0 subscriptions

About: Baycomp is a library for Bayesian comparison of classifiers, as a better alternative for null-hypothesis significance testing.

Changes:

Initial Announcement on mloss.org.


Logo Calculate Normalized Information Measures 1.0.0

by openpr_nlpr - December 2, 2011, 04:35:32 CET [ Project Homepage BibTeX Download ] 4342 views, 1033 downloads, 0 subscriptions

About: The toolbox is to calculate normalized information measures from a given m by (m+1) confusion matrix for objective evaluations of an abstaining classifier. It includes total 24 normalized information measures based on three groups of definitions, that is, mutual information, information divergence, and cross entropy.

Changes:

Initial Announcement on mloss.org.


Logo Deep Semantic Ranking Based Hashing 1.0

by openpr_nlpr - November 18, 2015, 07:25:16 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4325 views, 774 downloads, 0 subscriptions

About: This algorithm is described in Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval. See https://github.com/zhaofang0627/cuda-convnet-for-hashing

Changes:

Initial Announcement on mloss.org.


Logo SonS and MDSonS, Software for hierarchical clustering visualization V1

by marmarj3 - June 18, 2013, 12:18:05 CET [ Project Homepage BibTeX Download ] 4320 views, 1263 downloads, 0 subscriptions

About: This toolbox implements a novel visualization technique called Sectors on Sectors (SonS), and a extended version called Multidimensional Sectors on Sectors (MDSonS), for improving the interpretation of several data mining algorithms. The MDSonS method makes use of Multidimensional Scaling (MDS) to solve the main drawback of the previous method, namely, the lack of representing distances between pairs of clusters. These methods have been applied for visualizing the results of hierarchical clustering, Growing Hierarchical Self-Organizing Maps (GHSOM), classification trees and several manifolds. These methods make possible to extract all the existing relationships among centroids’ attributes at any hierarchy level.

Changes:

Initial Announcement on mloss.org.


Logo sparkcrowd 0.1.5

by enriquegrodrigo - December 13, 2017, 13:13:35 CET [ Project Homepage BibTeX Download ] 4287 views, 1151 downloads, 0 subscriptions

About: A Spark package implementing algorithms for learning from crowdsourced big data.

Changes:

Changes: - Minor improvements in code and documentation


Logo CPLVE 0.1

by wannesm - June 5, 2009, 13:06:42 CET [ BibTeX Download ] 4280 views, 1624 downloads, 0 subscriptions

About: Preparing

Changes:

Initial Announcement on mloss.org.


Logo seglearn 0.1

by dmbee - March 14, 2018, 21:45:46 CET [ Project Homepage BibTeX Download ] 4244 views, 1287 downloads, 0 subscriptions

About: Python module for machine learning multivariate time series

Changes:

Initial Announcement on mloss.org.


Logo pymanopt 0.1

by j_towns - April 7, 2016, 14:44:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4233 views, 886 downloads, 0 subscriptions

About: Python toolbox for manifold optimization with support for automatic differentiation

Changes:

Initial Announcement on mloss.org.


Logo How to Estimate the Regularization Parameter for Spectral Regression Discriminan 1.0

by openpr_nlpr - May 25, 2015, 03:26:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4223 views, 857 downloads, 0 subscriptions

About: Jie Gui et al., "How to estimate the regularization parameter for spectral regression discriminant analysis and its kernel version?", IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 2, pp. 211-223, 2014

Changes:

Initial Announcement on mloss.org.


Logo QSMM 1.16

by olegvol - July 29, 2014, 19:37:31 CET [ Project Homepage BibTeX Download ] 4208 views, 1091 downloads, 0 subscriptions

About: The implementation of adaptive probabilistic mappings.

Changes:

Initial Announcement on mloss.org.


Logo NearOED 1.0

by gabobert - July 11, 2013, 16:54:12 CET [ Project Homepage BibTeX Download ] 4203 views, 1207 downloads, 0 subscriptions

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.


Logo Half quadratic based Iterative Minimization for Robust Sparse Representation 1.0

by openpr_nlpr - June 3, 2013, 09:57:11 CET [ Project Homepage BibTeX Download ] 4198 views, 1115 downloads, 0 subscriptions

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 MIPS, The migrant implementation system 1.0

by thomasfannes - April 28, 2015, 15:07:05 CET [ Project Homepage BibTeX Download ] 4179 views, 1099 downloads, 0 subscriptions

About: MIPS is a software library for state-of-the-art graph mining algorithms. The library is platform independent, written in C++(03), and aims at implementing generic and efficient graph mining algorithms.

Changes:

description update


Showing Items 561-580 of 674 on page 29 of 34: First Previous 24 25 26 27 28 29 30 31 32 33 34 Next