Projects running under linux.
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Logo OpenNN 1.0

by Sergiointelnics - November 21, 2014, 13:15:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 52 views, 5 downloads, 1 subscription

About: OpenNN is an open source class library written in C++ which implements neural networks. The library has been designed to learn from both data sets and mathematical models.

Changes:

Initial Announcement on mloss.org.


Logo JMLR Sally 0.9.2

by konrad - November 19, 2014, 20:28:35 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21279 views, 4309 downloads, 2 subscriptions

About: A Tool for Embedding Strings in Vector Spaces

Changes:

Fixed severe bug in concurrent computation of blended n-grams.


Logo Harry 0.3.2

by konrad - November 19, 2014, 20:24:21 CET [ Project Homepage BibTeX Download ] 2413 views, 509 downloads, 2 subscriptions

About: A Tool for Measuring String Similarity

Changes:

Several minor bugfixes.


Logo libcmaes 0.9.3

by beniz - November 17, 2014, 14:04:10 CET [ Project Homepage BibTeX Download ] 2475 views, 517 downloads, 3 subscriptions

About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly non-linear and non-convex functions, using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability.

Changes:

This is an important update:

  • full support for surrogates, allowing optimization of costly objective functions, ref #57

  • integrated rankign SVM default surrogate, ref #83

  • Python bindings for surrogates, ref #75

  • more informed optimization status and error messages, ref #85

  • API for computing confidence intervals around optima, ref #30

  • API for computing 2D contour around optima, ref #31

  • new 'elitist' scheme for improved restart strategy useful on some rather difficult functions, ref #77

  • fixed Eigen namespace import, ref #62

  • fixed and added new parameter vector getter in Candidate, ref #84


Logo Lua MapReduce v0.3.6

by pakozm - November 15, 2014, 13:20:01 CET [ Project Homepage BibTeX Download ] 1804 views, 386 downloads, 3 subscriptions

About: Lua-MapReduce framework implemented in Lua using luamongo driver and MongoDB as storage. It follows Iterative MapReduce for training of Machine Learning statistical models.

Changes:
  • Improved tuple implementation.

Logo JMLR dlib ml 18.11

by davis685 - November 13, 2014, 23:42:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 85735 views, 14831 downloads, 2 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 contains mostly minor bug fixes and usability improvements, with the notable exception of new routines for extracting local-binary-pattern features from images and improved tools for learning distance metrics.


Logo Hub Miner 1.0

by nenadtomasev - November 12, 2014, 19:41:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 258 views, 36 downloads, 1 subscription

About: Hubness-aware Machine Learning for High-dimensional Data

Changes:

Initial Announcement on mloss.org.


Logo Armadillo library 4.500

by cu24gjf - November 4, 2014, 02:37:37 CET [ Project Homepage BibTeX Download ] 46653 views, 10054 downloads, 4 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:
  • faster handling of complex vectors by norm()
  • expanded chol() to optionally specify output matrix as upper or lower triangular
  • better handling of non-finite values when saving matrices as text files

Logo libcluster 2.1

by dsteinberg - October 31, 2014, 23:27:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 395 views, 68 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:

Initial Announcement on mloss.org.


Logo LogRegCrowds, Logistic Regression from Crowds 1.0

by fmpr - October 30, 2014, 19:10:23 CET [ Project Homepage BibTeX Download ] 322 views, 77 downloads, 2 subscriptions

About: LogReg-Crowds is a collection of Julia implementations of various approaches for learning a logistic regression model multiple annotators and crowds, namely the works of Raykar et al. (2010), Rodrigues et al. (2013) and Dawid and Skene (1979).

Changes:

Initial Announcement on mloss.org.


About: This library implements the Optimum-Path Forest classifier for unsupervised and supervised learning.

Changes:

Initial Announcement on mloss.org.


Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2184 views, 455 downloads, 1 subscription

About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.

Changes:

improved testing, improved documentation, windows compatibility, more algorithms


Logo BayesOpt, a Bayesian Optimization toolbox 0.7.2

by rmcantin - October 10, 2014, 19:12:59 CET [ Project Homepage BibTeX Download ] 9328 views, 1901 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 bugs and doc typos


Logo hca 0.61

by wbuntine - September 10, 2014, 03:33:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5333 views, 1045 downloads, 4 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrections to diagnostics and topic report. Correction to estimating alpha. Now estimating beta sometimes (when estimating phi).


Logo Somoclu 1.4

by peterwittek - September 5, 2014, 13:01:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4888 views, 924 downloads, 2 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.

Changes:
  • Better Windows support.
  • Completed CUDA support for Python and R interfaces.
  • Faster compilation by removing unnecessary flags for nvcc
  • Support for CUDA 6.5.
  • Bug fixes: R version no longer needs separate code.

Logo JMLR Darwin 1.8

by sgould - September 3, 2014, 08:42:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 29942 views, 6273 downloads, 4 subscriptions

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

Changes:

Version 1.8:

  • Added Superpixel Graph Label Transfer (nnGraph) Project project
  • Added Python scripts for automating some projects
  • Added ability to pre-process features on-the-fly with one drwnFeatureTransform when applying or learning another drwnFeatureTransform
  • Fixed race condition in Windows threading (thanks to Edison Guo)
  • Switched Windows and Linux to build against OpenCV 2.4.9
  • Changed drwnMAPInference::inference to return upper and lower energy bounds
  • Added pruneRounds function to drwnBoostedClassifier
  • Added drwnSLICSuperpixels function
  • Added drwnIndexQueue class
  • mexLearnClassifier and mexAnalyseClassifier now support integer label types
  • Bug fix in mexSaveSuperpixels to support single channel

Logo XGBoost v0.3.0

by crowwork - September 2, 2014, 02:43:31 CET [ Project Homepage BibTeX Download ] 3004 views, 556 downloads, 2 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.

Changes:

New features: - R support that is now on CRAN

  • Faster tree construction module

  • Support for boosting from initial predictions

  • Linear booster is now parallelized, using parallel coordinated descent.


Logo Salad 0.5.0

by chwress - August 22, 2014, 17:54:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4416 views, 804 downloads, 1 subscription

About: A Content Anomaly Detector based on n-Grams

Changes:

Lots and lots of cool new features and bugfixes ;)

  • Refinements to the user interface: This includes a progress indicator, colors, etc.
  • Determine the expected error (salad-inspect)
  • Enable the user to echo the used parametrization: salad [train|predict|inspect] --echo-params
  • Allow to set the input batch size as program argument: salad [train|predict|inspect] --batch-size
  • libsalad: The library allows to access salad's basic functions
  • Installers and precompiled binaries: Windows installer, Debian (ppa:chwress/salad) & RPM packages as well a generic linux installers.
  • Various minor bug fixes
  • Support for "length at end" zip files
  • Improve salad's usage in a 2-class setting: salad [train|predict|inspect] --input-filter

Logo QSMM 1.16

by olegvol - July 29, 2014, 19:37:31 CET [ Project Homepage BibTeX Download ] 588 views, 151 downloads, 3 subscriptions

About: The implementation of adaptive probabilistic mappings.

Changes:

Initial Announcement on mloss.org.


Logo Boosted Decision Trees and Lists 1.0.4

by melamed - July 25, 2014, 23:08:32 CET [ BibTeX Download ] 3012 views, 909 downloads, 3 subscriptions

About: Boosting algorithms for classification and regression, with many variations. Features include: Scalable and robust; Easily customizable loss functions; One-shot training for an entire regularization path; Continuous checkpointing; much more

Changes:
  • added ElasticNets as a regularization option
  • fixed some segfaults, memory leaks, and out-of-range errors, which were creeping in in some corner cases
  • added a couple of I/O optimizations

Showing Items 1-20 of 229 on page 1 of 12: 1 2 3 4 5 6 Next Last