Projects that are tagged with matlab.


Logo Armadillo library 8.500

by cu24gjf - April 23, 2018, 17:29:44 CET [ Project Homepage BibTeX Download ] 287465 views, 70717 downloads, 0 subscriptions

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About: Armadillo is a high quality C++ library for linear algebra & scientific computing, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products).

Changes:
  • faster handling of sparse matrices by kron() and repmat()
  • faster transpose of sparse matrices
  • faster element access in sparse matrices
  • faster row iterators for sparse matrices
  • faster handling of compound expressions by trace()
  • more efficient handling of aliasing in submatrix views
  • expanded normalise() to handle sparse matrices
  • expanded .transform() and .for_each() to handle sparse matrices
  • added reverse() for reversing order of elements
  • added repelem() for replicating elements
  • added roots() for finding the roots of a polynomial

Logo FEAST 2.0.0

by apocock - January 8, 2017, 00:49:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 76355 views, 12885 downloads, 0 subscriptions

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About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:

Major refactoring of FEAST to improve speed and portability.

  • FEAST now clones the input data if it's floating point and discretises it to unsigned ints once in a single pass. This improves the speed by about 30%.
  • FEAST now has unsigned int entry points which avoid this discretisation and are much faster if the data is already categorical.
  • Added weighted feature selection algorithms to FEAST which can be used for cost-sensitive feature selection.
  • Added a Java API using JNI.
  • FEAST now returns the internal score for each feature according to the criterion. Available in all three APIs.
  • Rearranged the repository to make it easier to work with. Header files are now in `include`, source in `src`, the MATLAB API is in `matlab/` and the Java API is in `java/`.
  • FEAST now compiles cleanly using `-std=c89 -Wall -Werror`.

Logo Universal Java Matrix Package 0.3.0

by arndt - July 31, 2015, 14:23:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 28945 views, 5535 downloads, 0 subscriptions

About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multi-threading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more.

Changes:

Updated to version 0.3.0


Logo JMLR SHOGUN 4.0.0

by sonne - February 5, 2015, 09:09:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 217864 views, 35367 downloads, 0 subscriptions

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About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line.

Changes:

This release features the work of our 8 GSoC 2014 students [student; mentors]:

  • OpenCV Integration and Computer Vision Applications [Abhijeet Kislay; Kevin Hughes]
  • Large-Scale Multi-Label Classification [Abinash Panda; Thoralf Klein]
  • Large-scale structured prediction with approximate inference [Jiaolong Xu; Shell Hu]
  • Essential Deep Learning Modules [Khaled Nasr; Sergey Lisitsyn, Theofanis Karaletsos]
  • Fundamental Machine Learning: decision trees, kernel density estimation [Parijat Mazumdar ; Fernando Iglesias]
  • Shogun Missionary & Shogun in Education [Saurabh Mahindre; Heiko Strathmann]
  • Testing and Measuring Variable Interactions With Kernels [Soumyajit De; Dino Sejdinovic, Heiko Strathmann]
  • Variational Learning for Gaussian Processes [Wu Lin; Heiko Strathmann, Emtiyaz Khan]

It also contains several cleanups and bugfixes:

Features

  • New Shogun project description [Heiko Strathmann]
  • ID3 algorithm for decision tree learning [Parijat Mazumdar]
  • New modes for PCA matrix factorizations: SVD & EVD, in-place or reallocating [Parijat Mazumdar]
  • Add Neural Networks with linear, logistic and softmax neurons [Khaled Nasr]
  • Add kernel multiclass strategy examples in multiclass notebook [Saurabh Mahindre]
  • Add decision trees notebook containing examples for ID3 algorithm [Parijat Mazumdar]
  • Add sudoku recognizer ipython notebook [Alejandro Hernandez]
  • Add in-place subsets on features, labels, and custom kernels [Heiko Strathmann]
  • Add Principal Component Analysis notebook [Abhijeet Kislay]
  • Add Multiple Kernel Learning notebook [Saurabh Mahindre]
  • Add Multi-Label classes to enable Multi-Label classification [Thoralf Klein]
  • Add rectified linear neurons, dropout and max-norm regularization to neural networks [Khaled Nasr]
  • Add C4.5 algorithm for multiclass classification using decision trees [Parijat Mazumdar]
  • Add support for arbitrary acyclic graph-structured neural networks [Khaled Nasr]
  • Add CART algorithm for classification and regression using decision trees [Parijat Mazumdar]
  • Add CHAID algorithm for multiclass classification and regression using decision trees [Parijat Mazumdar]
  • Add Convolutional Neural Networks [Khaled Nasr]
  • Add Random Forests algorithm for ensemble learning using CART [Parijat Mazumdar]
  • Add Restricted Botlzmann Machines [Khaled Nasr]
  • Add Stochastic Gradient Boosting algorithm for ensemble learning [Parijat Mazumdar]
  • Add Deep contractive and denoising autoencoders [Khaled Nasr]
  • Add Deep belief networks [Khaled Nasr]

Bugfixes

  • Fix reference counting bugs in CList when reference counting is on [Heiko Strathmann, Thoralf Klein, lambday]
  • Fix memory problem in PCA::apply_to_feature_matrix [Parijat Mazumdar]
  • Fix crash in LeastAngleRegression for the case D greater than N [Parijat Mazumdar]
  • Fix memory violations in bundle method solvers [Thoralf Klein]
  • Fix fail in library_mldatahdf5.cpp example when http://mldata.org is not working properly [Parijat Mazumdar]
  • Fix memory leaks in Vowpal Wabbit, LibSVMFile and KernelPCA [Thoralf Klein]
  • Fix memory and control flow issues discovered by Coverity [Thoralf Klein]
  • Fix R modular interface SWIG typemap (Requires SWIG >= 2.0.5) [Matt Huska]

Cleanup and API Changes

  • PCA now depends on Eigen3 instead of LAPACK [Parijat Mazumdar]
  • Removing redundant and fixing implicit imports [Thoralf Klein]
  • Hide many methods from SWIG, reducing compile memory by 500MiB [Heiko Strathmann, Fernando Iglesias, Thoralf Klein]

Logo BACOM2 1.0

by fydennis - October 24, 2014, 15:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8593 views, 2188 downloads, 0 subscriptions

About: revised version of BACOM

Changes:

Initial Announcement on mloss.org.


Logo RankSVM NC 1.0

by rflamary - July 10, 2014, 15:51:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11675 views, 2594 downloads, 0 subscriptions

About: This package is an implementation of a linear RankSVM solver with non-convex regularization.

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 ] 7299 views, 2124 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 MICP 1.04

by kay_brodersen - March 26, 2013, 12:42:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 19183 views, 3586 downloads, 0 subscriptions

About: This toolbox implements models for Bayesian mixed-effects inference on classification performance in hierarchical classification analyses.

Changes:

In addition to the existing MATLAB implementation, the toolbox now also contains an R package of the variational Bayesian algorithm for mixed-effects inference.


Logo VLFeat 0.9.16

by andreavedaldi - October 5, 2012, 18:44:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27104 views, 4845 downloads, 0 subscriptions

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 Sparse MultiTask Learning Toolbox 1.2

by rflamary - March 18, 2012, 11:31:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13133 views, 2835 downloads, 0 subscriptions

About: This package is a set of Matlab scripts that implements the algorithms described in the submitted paper: "Lp-Lq Sparse Linear and Sparse Multiple Kernel MultiTask Learning".

Changes:

Initial Announcement on mloss.org.


Logo Large margin filtering 0.9

by rflamary - February 18, 2012, 15:50:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11172 views, 2786 downloads, 0 subscriptions

About: Matlab SVM toolbox for learning large margin filters in signal or images.

Changes:

Initial Announcement on mloss.org.


Logo BCILAB 1.0-beta

by chkothe - January 6, 2012, 23:47:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14293 views, 2872 downloads, 0 subscriptions

About: MATLAB toolbox for advanced Brain-Computer Interface (BCI) research.

Changes:

Initial Announcement on mloss.org.


Logo mldata-utils 0.5.0

by sonne - April 8, 2011, 10:02:44 CET [ Project Homepage BibTeX Download ] 78129 views, 17017 downloads, 0 subscriptions

About: Tools to convert datasets from various formats to various formats, performance measures and API functions to communicate with mldata.org

Changes:
  • Change task file format, such that data splits can have a variable number items and put into up to 256 categories of training/validation/test/not used/...
  • Various bugfixes.

Logo Hidden Markov Support Vector Machines 0.2

by pramod - April 16, 2010, 17:27:41 CET [ BibTeX Download ] 11608 views, 3510 downloads, 0 subscriptions

About: This software is an implementation of Hidden Markov Support Vector Machines (HMSVMs).

Changes:

Initial Announcement on mloss.org.


Logo JMLR Matlab toolbox for submodular function optimization 2.0

by krausea - April 7, 2010, 09:53:40 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 33452 views, 9331 downloads, 0 subscriptions

About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others.

Changes:
  • Modified specification of optional parameters (using sfo_opt)
  • Added sfo_ls_lazy for maximizing nonnegative submodular functions
  • Added sfo_fn_infogain, sfo_fn_lincomb, sfo_fn_invert, ...
  • Added additional documentation and more examples
  • Now Octave ready

Logo Variational Inference for the Indian Buffet Process 0.1

by finale - May 4, 2009, 16:03:25 CET [ BibTeX BibTeX for corresponding Paper Download ] 16303 views, 3154 downloads, 0 subscriptions

About: Matlab code for performing variational inference in the Indian Buffet Process with a linear-Gaussian likelihood model.

Changes:

Initial Announcement on mloss.org.


Logo CVX, a modeling system for disciplined convex programming 1.2

by mcgrant - October 21, 2008, 23:55:08 CET [ Project Homepage BibTeX Download ] 12932 views, 2778 downloads, 0 subscriptions

About: CVX is a Matlab-based modeling system for convex optimization. CVX turns Matlab into a modeling language, allowing constraints and objectives to be specified using standard Matlab expression syntax. [...]

Changes:

Initial Announcement on mloss.org.


Logo SimpleMKL 0.5

by arakotom - June 11, 2008, 00:56:47 CET [ Project Homepage BibTeX Download ] 20388 views, 5386 downloads, 1 subscription

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About: Matlab Multiple Kernel Learning toolbox. Features : MKL for SVM Classification, Regression and MultiClass. It needs SVM-KM Toolbox

Changes:

Initial Announcement on mloss.org.


Logo SVM and Kernel Methods Toolbox 0.5

by arakotom - June 10, 2008, 21:29:39 CET [ Project Homepage BibTeX Download ] 17129 views, 4314 downloads, 0 subscriptions

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About: SVM Toolbox fully written in Matlab (even the QP solver). Features : SVM, MultiClassSVM, One-Class, SV Regression, AUC-SVM and Rankboost, 1-norm SVM, Regularization Networks, Kernel Basis Pursuit [...]

Changes:

Initial Announcement on mloss.org.


Logo Spider 1.71

by jaseweston - November 19, 2007, 15:51:59 CET [ Project Homepage BibTeX Download ] 12095 views, 3609 downloads, 0 subscriptions

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About: The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be [...]

Changes:

Initial Announcement on mloss.org.