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Logo Online Random Forests 0.11

by amirsaffari - October 3, 2009, 17:25:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12809 views, 2311 downloads, 1 subscription

About: This package implements the “Online Random Forests” (ORF) algorithm of Saffari et al., ICCV-OLCV 2009. This algorithm extends the offline Random Forests (RF) to learn from online training data samples. ORF is a multi-class classifier which is able to learn the classifier without 1-vs-all or 1-vs-1 binary decompositions.

Changes:

Initial Announcement on mloss.org.


Logo Lua MapReduce v0.4.0

by pakozm - December 23, 2015, 09:32:11 CET [ Project Homepage BibTeX Download ] 10918 views, 2301 downloads, 3 subscriptions

About: Lua-MapReduce framework implemented in Lua using luamongo driver and MongoDB as storage. It follows Iterative MapReduce for training of Machine Learning statistical models.

Changes:
  • Updated to work with luamongo v0.5.0, which uses C++ driver legacy-1.1.0

Logo SVQP 2

by leonbottou - January 31, 2009, 14:22:04 CET [ Project Homepage BibTeX Download ] 7069 views, 2301 downloads, 0 subscriptions

About: SVQP1 and SVQP2 are QP solvers for training SVM.

Changes:

Initial Announcement on mloss.org.


About: OpenGM is a free C++ template library, a command line tool and a set of MATLAB functions for optimization in higher order graphical models. Graphical models of any order and structure can be built either in C++ or in MATLAB, using simple and intuitive commands. These models can be stored in HDF5 files and subjected to state-of-the-art optimization algorithms via the OpenGM command line optimizer. All library functions can also be called directly from C++ code. OpenGM realizes the Inference Algorithm Interface (IAI), a concept that makes it easy for programmers to use their own algorithms and factor classes with OpenGM.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-bigrf 0.1-11

by r-cran-robot - May 16, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 10190 views, 2288 downloads, 0 subscriptions

About: Big Random Forests

Changes:

Fetched by r-cran-robot on 2015-11-01 00:00:04.072762


Logo VLFeat 0.9.16

by andreavedaldi - October 5, 2012, 18:44:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13409 views, 2276 downloads, 1 subscription

About: The VLFeat open source library implements popular computer vision algorithms including affine covariant feature detectors, HOG, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, and quick shift. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. The latest version of VLFeat is 0.9.16.

Changes:

VLFeat 0.9.16: Added VL_COVDET() (covariant feature detectors). This function implements the following detectors: DoG, Hessian, Harris Laplace, Hessian Laplace, Multiscale Hessian, Multiscale Harris. It also implements affine adaptation, estiamtion of feature orientation, computation of descriptors on the affine patches (including raw patches), and sourcing of custom feature frame. Addet the auxiliary function VL_PLOTSS(). This is the second point update supported by the PASCAL Harvest programme.

VLFeat 0.9.15: Added VL_HOG() (HOG features). Added VL_SVMPEGASOS() and a vastly improved SVM implementation. Added IHASHSUM (hashed counting). Improved INTHIST (integral histogram). Added VL_CUMMAX(). Improved the implementation of VL_ROC() and VL_PR(). Added VL_DET() (Detection Error Trade-off (DET) curves). Improved the verbosity control to AIB. Added support for Xcode 4.3, improved support for past and future Xcode versions. Completed the migration of the old test code in toolbox/test, moving the functionality to the new unit tests toolbox/xtest. Improved credits. This is the first point update supported by the PASCAL Harvest (several more to come shortly).


Logo Torch 3

by bengio - November 13, 2007, 01:38:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8669 views, 2273 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.


Logo LIBOCAS 0.93

by vf - June 20, 2010, 12:22:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14877 views, 2271 downloads, 2 subscriptions

About: The library implements Optimized Cutting Plane Algorithm (OCAS) for efficient training of linear SVM classifiers from large-scale data.

Changes:

Implemented COFFIN framework which allows efficient training of invariant image classifiers via virtual examples.


Logo Moses Decoder 2010-08-13

by oliver_wilson - September 3, 2010, 13:49:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7766 views, 2260 downloads, 0 comments, 1 subscription

About: Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices.

Changes:

Initial Announcement on mloss.org.


Logo SMIDAS 1.1

by ambujtewari - August 15, 2010, 18:51:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11075 views, 2245 downloads, 1 subscription

About: A stochastic variant of the mirror descent algorithm employing Langford and Zhang's truncated gradient idea to minimize L1 regularized loss minimization problems for classification and regression.

Changes:

Fixed major bug in implementation. The components of the iterate where the current example vector is zero were not being updated correctly. Thanks to Jonathan Chang for pointing out the error to us.


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