Projects supporting the hdf data format.

Logo Barista 0.2

by klemms - February 21, 2018, 15:51:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 983 views, 235 downloads, 1 subscription

About: a Graphical Tool for Designing and Training Deep Neural Networks


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Logo Armadillo library 8.400

by cu24gjf - February 20, 2018, 03:26:16 CET [ Project Homepage BibTeX Download ] 132545 views, 25172 downloads, 5 subscriptions

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About: Armadillo is a high quality C++ linear algebra library, 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).

  • faster handling of band matrices by solve() and chol()
  • faster incremental construction of sparse matrices via element access operators
  • faster diagonal views in sparse matrices
  • faster handling of sparse matrices by repmat()
  • faster loading of CSV files
  • faster gmm_diag class, for Gaussian mixture models with diagonal covariance matrices
  • speedups via expanded use of OpenMP by many element-wise functions
  • expanded kron() to handle sparse matrices
  • expanded index_min() and index_max() to handle cubes
  • expanded SpMat to save/load sparse matrices in coord format
  • expanded .save() to allow appending new datasets to existing HDF5 files
  • expanded .save()/.load() to allow specification of datasets within HDF5 files
  • expanded .each_slice() to optionally use OpenMP for multi-threaded execution
  • expanded clamp() to handle cubes
  • added submatrix & subcube iterators
  • added normpdf(), normcdf(), mvnrnd()
  • added chi2rnd(), wishrnd(), iwishrnd()
  • added gmm_full class, for Gaussian mixture models with full covariance matrices
  • added affmul() to simplify application of affine transformations
  • added intersect() for finding common elements in two vectors/matrices

Logo Indefinite Core Vector Machine 0.1

by fmschleif - January 5, 2018, 22:35:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1488 views, 388 downloads, 3 subscriptions

About: Armadillo/C++ implementation of the Indefinite Core Vector Machine


Some tiny errors in the Nystroem demo scripts - should be ok now Initial Announcement on

Logo JMLR MLPACK 2.2.5

by rcurtin - August 26, 2017, 06:07:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 101407 views, 18191 downloads, 6 subscriptions

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About: A scalable, fast C++ machine learning library, with emphasis on usability.


Released August 25, 2017.

  • Compilation fix for some systems (#1082).

  • Fix PARAM_INT_OUT() (#1100).

Logo BayesPy 0.4.1

by jluttine - November 2, 2015, 13:40:09 CET [ Project Homepage BibTeX Download ] 25052 views, 5379 downloads, 3 subscriptions

About: Variational Bayesian inference tools for Python

  • Define extra dependencies needed to build the documentation

Logo JMLR SHOGUN 4.0.0

by sonne - February 5, 2015, 09:09:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 142561 views, 20590 downloads, 6 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.


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:


  • 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]


  • 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 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 OptWok 0.3.1

by ong - May 2, 2013, 10:46:11 CET [ Project Homepage BibTeX Download ] 14910 views, 2932 downloads, 1 subscription

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier.

  • minor bugfix

Logo OpenGM 2 2.0.2 beta

by opengm - June 1, 2012, 14:33:53 CET [ Project Homepage BibTeX Download ] 5222 views, 1220 downloads, 1 subscription

About: A C++ Library for Discrete Graphical Models


Initial Announcement on

Logo Marray 2.2

by andres - July 6, 2011, 01:27:44 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5815 views, 1344 downloads, 1 subscription

About: Fast Runtime-Flexible Multi-dimensional Arrays and Views for C++


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Logo svn-r1070-Apr-2011

by sonne - April 8, 2011, 10:15:49 CET [ Project Homepage BibTeX Download ] 6574 views, 1589 downloads, 1 subscription

About: The source code of the site - a community portal for machine learning data sets.


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Logo mldata-utils 0.5.0

by sonne - April 8, 2011, 10:02:44 CET [ Project Homepage BibTeX Download ] 42545 views, 8938 downloads, 1 subscription

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

  • 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.

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.


Initial Announcement on