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Logo JMLR dlib ml 19.0

by davis685 - June 25, 2016, 23:04:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 141418 views, 23088 downloads, 4 subscriptions

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.

Changes:

This release adds a deep learning toolkit to dlib that has a clean and fully documented C++11 API. It also includes CPU and GPU support, binds to cuDNN, can train on multiple GPUs at a time, and comes with a pretrained imagenet model based on ResNet34.

The release also adds a number of other improvements such as new elastic net regularized solvers and QP solvers, improved MATLAB binding tools, and other usability tweaks and optimizations.


Logo JMLR Information Theoretical Estimators 0.63

by szzoli - June 9, 2016, 23:42:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 101628 views, 19568 downloads, 3 subscriptions

About: ITE (Information Theoretical Estimators) is capable of estimating many different variants of entropy, mutual information, divergence, association measures, cross quantities and kernels on distributions. Thanks to its highly modular design, ITE supports additionally (i) the combinations of the estimation techniques, (ii) the easy construction and embedding of novel information theoretical estimators, and (iii) their immediate application in information theoretical optimization problems.

Changes:
  • Conditional Shannon entropy estimation: added.

  • Conditional Shannon mutual information estimation: included.


Logo r-cran-caret 6.0-68

by r-cran-robot - April 10, 2016, 00:00:00 CET [ Project Homepage BibTeX Download ] 94297 views, 18784 downloads, 3 subscriptions

About: Classification and Regression Training

Changes:

Fetched by r-cran-robot on 2016-06-01 00:00:04.755170


Logo Armadillo library 6.700

by cu24gjf - April 24, 2016, 05:08:11 CET [ Project Homepage BibTeX Download ] 83839 views, 17048 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).

Changes:
  • added trapz() for numerical integration
  • added logmat() for calcuating the matrix logarithm
  • added approx_equal() for determining approximate equality
  • added regspace() for generating vectors with regularly spaced elements
  • added logspace() for generating vectors with logarithmically spaced elements
  • expanded .save() and .load() with hdf5_binary_trans file type, to save/load data with columns transposed to rows
  • fixes for trunc_log() and trunc_exp()

Logo JMLR SHOGUN 4.0.0

by sonne - February 5, 2015, 09:09:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 110523 views, 15744 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.

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 OpenOpt 0.54

by Dmitrey - June 15, 2014, 14:50:37 CET [ Project Homepage BibTeX Download ] 61706 views, 12880 downloads, 3 subscriptions

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About: Universal Python-written numerical optimization toolbox. Problems: NLP, LP, QP, NSP, MILP, LSP, LLSP, MMP, GLP, SLE, MOP etc; general logical constraints, categorical variables, automatic differentiation, stochastic programming, interval analysis, many other goodies

Changes:

http://openopt.org/Changelog


Logo MLPY Machine Learning Py 3.5.0

by albanese - March 15, 2012, 09:52:41 CET [ Project Homepage BibTeX Download ] 69317 views, 12834 downloads, 2 subscriptions

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About: mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL.

Changes:

New features:

  • LibSvm(): pred_probability() now returns probability estimates; pred_values() added
  • LibLinear(): pred_values() and pred_probability() added
  • dtw_std: squared Euclidean option added
  • LCS for series composed by real values (lcs_real()) added
  • Documentation

Fix:

  • wavelet submodule: cwt(): it returned only real values in morlet and poul
  • IRelief(): remove np. in learn()
  • fix rfe_kfda and rfe_w2 when p=1

Logo MyMediaLite 3.10

by zenog - October 8, 2013, 22:29:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 68053 views, 12444 downloads, 1 subscription

About: MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms.

Changes:

Mostly bug fixes.

For details see: https://github.com/zenogantner/MyMediaLite/blob/master/doc/Changes


Logo JMLR MLPACK 2.0.2

by rcurtin - June 20, 2016, 22:23:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 59488 views, 10922 downloads, 6 subscriptions

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

Changes:
  • Added the function LSHSearch::Projections(), which returns an arma::cube with each projection table in a slice (#663). Instead of Projection(i), you should now use Projections().slice(i).
  • A new constructor has been added to LSHSearch that creates objects using projection tables provided in an arma::cube (#663).
  • LSHSearch projection tables refactored for speed (#675).
  • Handle zero-variance dimensions in DET (#515).
  • Add MiniBatchSGD optimizer (src/mlpack/core/optimizers/minibatch_sgd/) and allow its use in mlpack_logistic_regression and mlpack_nca programs.
  • Add better backtrace support from Grzegorz Krajewski for Log::Fatal messages when compiled with debugging and profiling symbols. This requires libbfd and libdl to be present during compilation.
  • CosineTree test fix from Mikhail Lozhnikov (#358).
  • Fixed HMM initial state estimation (#600).
  • Changed versioning macros _MLPACKVERSION_MAJOR, _MLPACKVERSION_MINOR, and _MLPACKVERSION_PATCH to MLPACK_VERSION_MAJOR, MLPACK_VERSION_MINOR, and MLPACK_VERSION_PATCH. The old names will remain in place until mlpack 3.0.0.
  • Renamed mlpack_allknn, mlpack_allkfn, and mlpack_allkrann to mlpack_knn, mlpack_kfn, and mlpack_krann. The mlpack_allknn, mlpack_allkfn, and mlpack_allkrann programs will remain as copies until mlpack 3.0.0.
  • Add --random_initialization option to mlpack_hmm_train, for use when no labels are provided.
  • Add --kill_empty_clusters option to mlpack_kmeans and KillEmptyClusters policy for the KMeans class (#595, #596).

Logo JMLR Darwin 1.9

by sgould - September 8, 2015, 06:50:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 49516 views, 10367 downloads, 4 subscriptions

About: A platform-independent C++ framework for machine learning, graphical models, and computer vision research and development.

Changes:

Version 1.9:

  • Replaced drwnInPaint class with drwnImageInPainter class and added inPaint application
  • Added function to read CIFAR-10 and CIFAR-100 style datasets (see http://www.cs.utoronto.ca/~kriz/cifar.html)
  • Added drwnMaskedPatchMatch, drwnBasicPatchMatch, drwnSelfPatchMatch and basicPatchMatch application
  • drwnPatchMatchGraph now allows multiple matches to the same image
  • Upgraded wxWidgets to 3.0.2 (problems on Mac OS X)
  • Switched Mac OS X compilation to libc++ instead of libstdc++
  • Added Python scripts for running experiments and regression tests
  • Refactored drwnGrabCutInstance class to support both GMM and colour histogram model
  • Added cacheSortIndex to drwnDecisionTree for trading-off speed versus memory usage
  • Added mexLoadPatchMatchGraph for loading drwnPatchMatchGraph objects into Matlab
  • Improved documentation, other bug fixes and performance improvements

Showing Items 1-10 of 622 on page 1 of 63: 1 2 3 4 5 6 Next Last