Projects running under windows.
Showing Items 1-20 of 193 on page 1 of 10: 1 2 3 4 5 6 Next Last

Logo Armadillo library 6.100

by cu24gjf - October 3, 2015, 07:12:38 CET [ Project Homepage BibTeX Download ] 64426 views, 13090 downloads, 5 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 3 votes)

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).

  • faster norm() and normalise() when using Intel MKL, ATLAS or OpenBLAS
  • faster handling of compound expressions by join_rows() and join_cols()
  • added Schur decomposition: schur()
  • added .each_slice() for repeated matrix operations on each slice of a cube
  • expanded join_slices() to handle joining cubes with matrices
  • expanded .each_col() and .each_row() to handle out-of-place operations
  • stricter handling of matrix objects by hist() and histc()
  • Cube class now delays allocation of .slice() related structures until needed

Logo Somoclu 1.5

by peterwittek - September 30, 2015, 13:27:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8886 views, 1735 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.

  • New: Python interface has visual capabilities.
  • New: Option for hexagonal grid.
  • New: Option for requesting compact support in updating the map.
  • New: Python, R, and MATLAB interfaces now allow passing an initial codebook.
  • Changed: Reduced memory use in calculating U-matrices.
  • Changed: Build system rebuilt and simplified.

Logo DiffSharp 0.7.0

by gbaydin - September 29, 2015, 14:09:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2941 views, 610 downloads, 3 subscriptions

About: DiffSharp is an automatic differentiation (AD) library providing gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products. It allows exact and efficient calculation of derivatives, with support for nesting.


Version 0.7.0 is a reimplementation of the library with support for linear algebra primitives, BLAS/LAPACK, 32- and 64-bit precision and different CPU/GPU backends

Changed: Namespaces have been reorganized and simplified. This is a breaking change. There is now just one AD implementation, under DiffSharp.AD (with DiffSharp.AD.Float32 and DiffSharp.AD.Float64 variants, see below). This internally makes use of forward or reverse AD as needed.

Added: Support for 32 bit (single precision) and 64 bit (double precision) floating point operations. All modules have Float32 and Float64 versions providing the same functionality with the specified precision. 32 bit floating point operations are significantly faster (as much as twice as fast) on many current systems.

Added: DiffSharp now uses the OpenBLAS library by default for linear algebra operations. The AD operations with the types D for scalars, DV for vectors, and DM for matrices use the underlying linear algebra backend for highly optimized native BLAS and LAPACK operations. For non-BLAS operations (such as Hadamard products and matrix transpose), parallel implementations in managed code are used. All operations with the D, DV, and DM types support forward and reverse nested AD up to any level. This also paves the way for GPU backends (CUDA/CuBLAS) which will be introduced in following releases. Please see the documentation and API reference for information about how to use the D, DV, and DM types. (Deprecated: The FsAlg generic linear algebra library and the Vector<'T> and Matrix<'T> types are no longer used.)

Fixed: Reverse mode AD has been reimplemented in a tail-recursive way for better performance and preventing StackOverflow exceptions encountered in previous versions.

Changed: The library now uses F# 4.0 (FSharp.Core

Changed: The library is now 64 bit only, meaning that users should set "x64" as the platform target for all build configurations.

Fixed: Overall bug fixes.

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 ] 3563 views, 893 downloads, 1 subscription

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.


Initial Announcement on

Logo MLweb 0.1.1

by lauerfab - September 22, 2015, 09:57:44 CET [ Project Homepage BibTeX Download ] 659 views, 169 downloads, 2 subscriptions

About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlab-like development environment.

  • Smaller source package
  • Fix Makefile
  • Fix MathJax path

Logo WEKA 3.7.13

by mhall - September 11, 2015, 04:55:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 49501 views, 7318 downloads, 4 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 6 votes)

About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...]


In core weka:

  • Numerically stable implementation of variance calculation in core Weka classes - thanks to Benjamin Weber
  • Unified expression parsing framework (with compiled expressions) is now employed by filters and tools that use mathematical/logical expressions - thanks to Benjamin Weber
  • Developers can now specify GUI and command-line options for their Weka schemes via a new unified annotation-based mechanism
  • ClassConditionalProbabilities filter - replaces the value of a nominal attribute in a given instance with its probability given each of the possible class values
  • GUI package manager's available list now shows both packages that are not currently installed, and those installed packages for which there is a more recent version available that is compatible with the base version of Weka being used
  • ReplaceWithMissingValue filter - allows values to be randomly (with a user-specified probability) replaced with missing values. Useful for experimenting with methods for imputing missing values
  • WrapperSubsetEval can now use plugin evaluation metrics

In packages:

  • alternatingModelTrees package - alternating trees for regression
  • timeSeriesFilters package, contributed by Benjamin Weber
  • distributedWekaSpark package - wrapper for distributed Weka on Spark
  • wekaPython package - execution of CPython scripts and wrapper classifier/clusterer for Scikit Learn schemes
  • MLRClassifier in RPlugin now provides access to almost all classification and regression learners in MLR 2.4

Logo JMLR Darwin 1.9

by sgould - September 8, 2015, 06:50:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 39829 views, 8262 downloads, 4 subscriptions

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


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
  • 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 jLDADMM 1.0

by dqnguyen - August 19, 2015, 12:52:36 CET [ Project Homepage BibTeX Download ] 581 views, 106 downloads, 2 subscriptions

About: The Java package jLDADMM is released to provide alternative choices for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models.


Initial Announcement on

Logo JMLR dlib ml 18.17

by davis685 - August 16, 2015, 04:33:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 113617 views, 19019 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.


This release adds new clustering tools as well as upgrades the shape_predictor to allow training on datasets with missing landmarks. It also includes bug fixes and minor usability improvements.

Logo PyScriptClassifier 0.0.1

by cjb60 - August 15, 2015, 05:14:59 CET [ Project Homepage BibTeX Download ] 521 views, 147 downloads, 1 subscription

About: Easily prototype WEKA classifiers using Python scripts.


Initial Announcement on

Logo OpenNN 2.2

by Sergiointelnics - August 10, 2015, 16:56:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3413 views, 599 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.


New algorithms, correction of bugs.

Logo JMLR libDAI 0.3.2

by jorism - July 17, 2015, 15:59:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 42293 views, 7886 downloads, 4 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarWhole Star
(based on 1 vote)

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.


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

Logo ABACOC Adaptive Ball Cover for Classification 2.0

by kikot - May 29, 2015, 11:57:28 CET [ BibTeX BibTeX for corresponding Paper Download ] 2744 views, 678 downloads, 3 subscriptions

About: Incremental (Online) Nonparametric Classifier. You can classify both points (standard) or matrices (multivariate time series). Java and Matlab code already available.


version 2: parameterless system, constant model size, prediction confidence (for active learning).

NEW!! C++ version at:

Logo Probabilistic Classification Vector Machine 0.21

by fmschleif - May 26, 2015, 16:24:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2071 views, 493 downloads, 3 subscriptions

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


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)

About: Jie Gui et al., "How to estimate the regularization parameter for spectral regression discriminant analysis and its kernel version?", IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 2, pp. 211-223, 2014


Initial Announcement on

About: Jie Gui, Zhenan Sun, Guangqi Hou, Tieniu Tan, "An optimal set of code words and correntropy for rotated least squares regression", International Joint Conference on Biometrics, 2014, pp. 1-6


Initial Announcement on

Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 9105 views, 1782 downloads, 3 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. The newest version of xgboost now supports distributed learning on various platforms such as hadoop, mpi and scales to even larger problems

  • Distributed version of xgboost that runs on YARN, scales to billions of examples

  • Direct save/load data and model from/to S3 and HDFS

  • Feature importance visualization in R module, by Michael Benesty

  • Predict leaf index

  • Poisson regression for counts data

  • Early stopping option in training

  • Native save load support in R and python

  • xgboost models now can be saved using save/load in R

  • xgboost python model is now pickable

  • sklearn wrapper is supported in python module

  • Experimental External memory version

Logo lomo feature extraction and xqda metric learning for person reidentification 1.0

by openpr_nlpr - May 6, 2015, 11:38:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1141 views, 176 downloads, 3 subscriptions

Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty Star
(based on 1 vote)

About: This MATLAB package provides the LOMO feature extraction and the XQDA metric learning algorithms proposed in our CVPR 2015 paper. It is fast, and effective for person re-identification. For more details, please visit


Initial Announcement on

Logo BLOG 0.9.1

by jxwuyi - April 27, 2015, 06:52:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1154 views, 242 downloads, 3 subscriptions

About: Bayesian Logic (BLOG) is a probabilistic modeling language. It is designed for representing relations and uncertainties among real world objects.


Initial Announcement on

Logo FsAlg 0.5.4

by gbaydin - April 25, 2015, 02:11:03 CET [ Project Homepage BibTeX Download ] 802 views, 246 downloads, 1 subscription

About: FsAlg is a linear algebra library that supports generic types.


Initial Announcement on

Showing Items 1-20 of 193 on page 1 of 10: 1 2 3 4 5 6 Next Last