20 projects found that use c++ as the programming language.
Showing Items 1-20 of 192 on page 1 of 10: 1 2 3 4 5 6 Next Last

Logo Armadillo library 6.500

by cu24gjf - January 27, 2016, 12:11:29 CET [ Project Homepage BibTeX Download ] 74324 views, 15107 downloads, 5 subscriptions

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About: Armadillo is a template C++ linear algebra library aiming towards a good balance between speed and ease of use, with a function syntax similar to MATLAB. Matrix decompositions are provided through optional integration with LAPACK, or one of its high performance drop-in replacements (eg. Intel MKL, OpenBLAS).

Changes:
  • added stand-alone kmeans() function for clustering data
  • added trunc(), ind2sub() and sub2ind()
  • added conv2() for 2D convolution
  • extended conv() to optionally provide central convolution
  • expanded each_col(), each_row() and each_slice() to handle C++11 lambda functions
  • faster handling of multiply-and-accumulate by accu() when using Intel MKL, ATLAS or OpenBLAS
  • fixes for corner cases in gmm_diag class

Logo libcluster 2.2

by dsteinberg - January 24, 2016, 03:32:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2353 views, 520 downloads, 2 subscriptions

About: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.

Changes:

Python 2 & 3 interface fixes and minor updates. Now uses Travis-CI as well.


Logo APCluster 1.4.2

by UBod - January 19, 2016, 13:56:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 28040 views, 4927 downloads, 3 subscriptions

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About: The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The package further provides leveraged affinity propagation, exemplar-based agglomerative clustering, and various tools for visual analysis of clustering results.

Changes:
  • switched sequence kernel example in vignette from 'kernlab' to 'kebabs' package
  • workaround to ensure that all apcluster*() methods are able to process KernelMatrix objects (cf. kebabs package)
  • replaced data set ch22Promoters by plain text file (FASTA format) in inst/examples
  • bug fix in the heatmap() method
  • vignette engine changed from Sweave to knitr

Logo pattern recognition tool 1.0

by openpr_nlpr - January 19, 2016, 03:54:11 CET [ Project Homepage BibTeX Download ] 366 views, 123 downloads, 3 subscriptions

About: a tool for marking samples in images for database building, also including algorithm of LBP,HOG,and classifiers of SVM (six kernels), adaboost,BP and convolutional networks, extreme learning machine.

Changes:

Initial Announcement on mloss.org.


Logo JMLR MLPACK 2.0.0

by rcurtin - January 11, 2016, 17:24:35 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 53076 views, 9934 downloads, 6 subscriptions

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

Changes:
  • Removed overclustering support from k-means because it is not well-tested, may be buggy, and is (I think) unused. If this was support you were using, open a bug or get in touch with us; it would not be hard for us to reimplement it.
  • Refactored KMeans to allow different types of Lloyd iterations.
  • Added implementations of k-means: Elkan's algorithm, Hamerly's algorithm, Pelleg-Moore's algorithm, and the DTNN (dual-tree nearest neighbor) algorithm.
  • Significant acceleration of LRSDP via the use of accu(a % b) instead of trace(a * b).
  • Added MatrixCompletion class (matrix_completion), which performs nuclear norm minimization to fill unknown values of an input matrix.
  • No more dependence on Boost.Random; now we use C++11 STL random support.
  • Add softmax regression, contributed by Siddharth Agrawal and QiaoAn Chen.
  • Changed NeighborSearch, RangeSearch, FastMKS, LSH, and RASearch API; these classes now take the query sets in the Search() method, instead of in the constructor.
  • Use OpenMP, if available. For now OpenMP support is only available in the DET training code.
  • Add support for predicting new test point values to LARS and the command-line 'lars' program.
  • Add serialization support for Perceptron and LogisticRegression.
  • Refactor SoftmaxRegression to predict into an arma::Row object, and add a softmax_regression program.
  • Refactor LSH to allow loading and saving of models.
  • ToString() is removed entirely (#487).
  • Add --input_model_file and --output_model_file options to appropriate machine learning algorithms.
  • Rename all executables to start with an "mlpack" prefix (#229).

See also https://mailman.cc.gatech.edu/pipermail/mlpack/2015-December/000706.html for more information.


Logo Somoclu 1.6

by peterwittek - January 11, 2016, 09:40:34 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12435 views, 2463 downloads, 3 subscriptions

About: Somoclu is a massively parallel implementation of self-organizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Apart from a command line interface, Python, R, and MATLAB are supported.

Changes:
  • New: R wrapper integrates with kohonen package.
  • New: MATLAB wrapper integrates with soomtoolbox.
  • New: Better handling of CUDA compilation in the Python interface.
  • Changed: Throws an exception if GPU kernel is requested, but it was compiled without it. The earlier behaviour quietly defaulted to the CPU kernel.

Logo MIToolbox 2.1.2

by apocock - January 10, 2016, 22:19:30 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 22433 views, 4016 downloads, 2 subscriptions

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features.

Changes:

Relicensed as BSD. Added checks to catch MATLAB inputs that aren't doubles.


Logo NaN toolbox 2.8.5

by schloegl - January 5, 2016, 12:10:15 CET [ Project Homepage BibTeX Download ] 41967 views, 8721 downloads, 3 subscriptions

About: NaN-toolbox is a statistics and machine learning toolbox for handling data with and without missing values.

Changes:

Changes in v.2.8.5 - bug fix: trimmean - compiler support for gcc-5 and clang - fix typos

For details see the CHANGELOG at http://pub.ist.ac.at/~schloegl/matlab/NaN/CHANGELOG


Logo BayesOpt, a Bayesian Optimization toolbox 0.8.2

by rmcantin - December 9, 2015, 04:53:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 19510 views, 3815 downloads, 4 subscriptions

About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinear-optimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python.

Changes:

-Fixed bug in save/restore. -Fixed bug in initial design.


Logo A Pattern Recognizer In Lua with ANNs v0.4.1

by pakozm - December 3, 2015, 15:01:36 CET [ Project Homepage BibTeX Download ] 6289 views, 1450 downloads, 2 subscriptions

About: APRIL-ANN toolkit (A Pattern Recognizer In Lua with Artificial Neural Networks). This toolkit incorporates ANN algorithms (as dropout, stacked denoising auto-encoders, convolutional neural networks), with other pattern recognition methods as hidden makov models (HMMs) among others.

Changes:
  • Updated home repository link to follow april-org github organization.
  • Improved serialize/deserialize functions, reimplemented all the serialization procedure.
  • Added exceptions support to LuaPkg and APRIL-ANN, allowing to capture C++ errors into Lua code.
  • Added set class.
  • Added series class.
  • Added data_frame class, similar to Python Pandas DataFrame.
  • Serialization and deserilization have been updated with more robust and reusable API, implemented in util.serialize() and util.deserialize() functions.
  • Added matrix.ext.broadcast utility (similar to broadcast in numpy).
  • Added ProbablisitcMatrixANNComponent, which allow to implement probabilistic mixtures of posteriors and/or likelihoods.
  • Added batch normalization ANN component.
  • Allowing matrix.join to add new axis.
  • Added methods prod(), cumsum() and cumprod() at matrix classes.
  • Added methods count_eq() and count_neq() at matrix classes.
  • Serializable objects API have been augmented with methods ctor_name() and
    ctor_params() in Lua, refered to luaCtorName() and luaCtorParams() in C++.
  • Added cast.to to dynamic cast C++ objects pushed into Lua, allowing to convert base class objects into any of its derived classes.
  • Added matrix.sparse as valid values for targets in ann.loss.mse and
    ann.loss.cross_entropy.
  • Changed matrix metamethods __index and __newindex, allowing to use
    matrix objects with standard Lua operator[].
  • Added matrix.masked_fill and matrix.masked_copy matrix.
  • Added matrix.indexed_fill and matrix.indexed_copy matrix.
  • Added ann.components.probabilistic_matrix, and its corresponding specializations ann.components.left_probabilistic_matrix and
    ann.components.right_probabilistic_matrix.
  • Added operator[] in the right side of matrix operations.
  • Added ann.components.transpose.
  • Added max_gradients_norm in traianble.supervised_trainer, to avoid gradients exploding.
  • Added ann.components.actf.sparse_logistic a logistic activation function with sparsity penalty.
  • Simplified math.add, math.sub, ... and other math extensions for reductions, their original behavior can be emulated by using bind function.
  • Added bind function to freeze any positional argument of any Lua function.
  • Function stats.boot uses multiple_unpack to allow a table of sizes and the generation of multiple index matrices.
  • Added multiple_unpack Lua function.
  • Added __tostring metamethod to numeric memory blocks in Lua.
  • Added dataset.token.sparse_matrix, a dataset which allow to traverse by rows a sparse matrix instance.
  • Added matrix.sparse.builders.dok, a builder which uses the Dictionary-of-Keys format to construct a sparse matrix from scratch.
  • Added method data to numeric matrix classes.
  • Added methods values, indices, first_index to sparse matrix class.
  • Fixed bugs when reading bad formed CSV files.
  • Fixed bugs at statistical distributions.
  • FloatRGB bug solved on equal (+=, -=, ...) operators. This bug affected ImageRGB operations such as resize.
  • Solved problems when chaining methods in Lua, some objects end to be garbage collected.
  • Improved support of strings in auto-completion (rlcompleter package).
  • Solved bug at SparseMatrix<T> when reading it from a file.
  • Solved bug in Image<T>::rotate90_cw methods.
  • Solved bug in SparseMatrix::toDense() method.

C/C++

  • Better LuaTable accessors, using [] operator.
  • Implementation of matrix __index, __newindex and __call metamethods in C++.
  • Implementation of matProd(), matCumSum() and matCumProd() functions.
  • Implementation of matCountEq() and matCountNeq() functions for
    Matrix<T>.
  • Updated matrix_ext_operations.h to change API of matrix operations. All functions have been overloaded to accept an in-place operation and another version which receives a destination matrix.
  • Adding iterators to language models.
  • Added MatrixScalarMap2 which receives as input2 a SparaseMatrix instance. This functions needs to be generalized to work with CPU and CUDA.
  • The method SparseMatrix<T>::fromDenseMatrix() uses a DOKBuilder object to build the sparse matrix.
  • The conversion of a Matrix<T> into a SparseMatrix<T> has been changed from a constructor overload to the static method
    SparseMatrix<T>::fromDenseMatrix().
  • Added support for IPyLua.
  • Optimized matrix access for confusion matrix.
  • Minor changes in class.lua.
  • Improved binding to avoid multiple object copies when pushing C++ objects.
  • Added Git commit hash and compilation time.

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 ] 732 views, 149 downloads, 3 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.


About: Efficient and Flexible Distributed/Mobile Deep Learning Framework, for python, R, Julia and more

Changes:

This version comes with Distributed and Mobile Examples


Logo Probabilistic Classification Vector Machine 0.22

by fmschleif - November 10, 2015, 13:16:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3823 views, 849 downloads, 3 subscriptions

About: PCVM library a c++/armadillo implementation of the Probabilistic Classification Vector Machine.

Changes:

30.10.2015 * code has been revised in some places fixing also some errors different multiclass schemes and hdf5 file support added. Some speed ups and memory savings by better handling of intermediate objects.

27.05.2015: - Matlab binding under Windows available. Added a solution file for VS'2013 express to compile a matlab mex binding. Can not yet confirm that under windows the code is really using multiple cores (under linux it does)

29.04.2015 * added an implementation of the Nystroem based PCVM includes: Nystroem based singular value decomposition (SVD), eigenvalue decomposition (EVD) and pseudo-inverse calculation (PINV)

22.04.2015 * implementation of the PCVM released


Logo KeBABS 1.4.1

by UBod - November 3, 2015, 11:33:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9835 views, 1784 downloads, 3 subscriptions

About: Kernel-Based Analysis of Biological Sequences

Changes:
  • new method to compute prediction profiles from models trained with mixture kernels
  • correction for position specific kernel with offsets
  • corrections for prediction profile of motif kernel
  • additional hint on help page of kbsvm

Logo JMLR dlib ml 18.18

by davis685 - October 29, 2015, 01:48:44 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 128481 views, 21253 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 has focused on build system improvements, both for the Python API and C++ builds using CMake. This includes adding a setup.py script for installing the dlib Python API as well as a make install target for installing a C++ shared library for non-Python use.


Logo Chalearn gesture challenge code by jun wan 2.0

by joewan - September 29, 2015, 08:50:22 CET [ BibTeX BibTeX for corresponding Paper Download ] 4694 views, 1166 downloads, 2 subscriptions

About: This code is provided by Jun Wan. It is used in the Chalearn one-shot learning gesture challenge (round 2). This code includes: bag of features, 3D MoSIFT-based features (i.e. 3D MoSIFT, 3D EMoSIFT and 3D SMoSIFT), and the MFSK feature.

Changes:

Initial Announcement on mloss.org.


Logo JMLR Darwin 1.9

by sgould - September 8, 2015, 06:50:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 44863 views, 9347 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

Logo OpenNN 2.2

by Sergiointelnics - August 10, 2015, 16:56:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4523 views, 794 downloads, 3 subscriptions

About: OpenNN is an open source class library written in C++ programming language which implements neural networks, a main area of deep learning research. The library has been designed to learn from both data sets and mathematical models.

Changes:

New algorithms, correction of bugs.


Logo libnabo 1.0.6

by smagnenat - August 5, 2015, 12:16:40 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10925 views, 2411 downloads, 3 subscriptions

About: libnabo is a fast K Nearset Neighbor library for low-dimensional spaces.

Changes:
  • Reset point indices of results with distances exceeding threshold (#23, #24)
  • Fine tune the find_package() capability and add uninstall target (#22)
  • Fixed compiler warning (#18)
  • Added OpenMP support (#20, #21)
  • Build type tuning (#19)
  • Fix: terminal comma in enum requires C++11
  • Fix UBSAN error calculating maxNodeCount (#16, #17)
  • Fixed tiny (yet significant) error in the Python doc strings (#15)
  • Compile static lib with PIC (#14)
  • Added configure scripts for full catkinization
  • Catkinization of libnabo (following REP136)
  • Update README.md Added Simon as the maintainer.
  • [test] use CLOCK_PROF for NetBSD build
  • Fixed CppCheck warning. Fix broken install when doxygen is not found
  • Fix cmake stylistic issue
  • Make python install respect custom CMAKE_INSTALL_PREFIX
  • Fix broken install when doxygen is not found

Logo JMLR libDAI 0.3.2

by jorism - July 17, 2015, 15:59:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 46112 views, 8557 downloads, 4 subscriptions

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About: libDAI provides free & open source implementations of various (approximate) inference methods for graphical models with discrete variables, including Bayesian networks and Markov Random Fields.

Changes:

Release 0.3.2 fixes various bugs and adds GLC (Generalized Loop Corrections) written by Siamak Ravanbakhsh.


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