Projects running under windows.
Showing Items 1-20 of 189 on page 1 of 10: 1 2 3 4 5 6 Next Last

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

Changes:

Initial Announcement on mloss.org.


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

Changes:

Initial Announcement on mloss.org.


Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 6493 views, 1248 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

Changes:
  • 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


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 http://www.cbsr.ia.ac.cn/users/scliao/projects/lomo_xqda/.

Changes:

Initial Announcement on mloss.org.


Logo JMLR dlib ml 18.15

by davis685 - April 30, 2015, 03:49:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 100084 views, 17174 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 an implementation of the least-squares policy iteration algorithm, a tool for plotting 3D point clouds, and a few bug fixes and usability improvements.


Logo BLOG 0.9.1

by jxwuyi - April 27, 2015, 06:52:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 451 views, 87 downloads, 3 subscriptions

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

Changes:

Initial Announcement on mloss.org.


Logo DiffSharp 0.6.0

by gbaydin - April 27, 2015, 01:47:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 367 views, 60 downloads, 1 subscription

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.

Changes:

Initial Announcement on mloss.org.


Logo FsAlg 0.5.4

by gbaydin - April 25, 2015, 02:11:03 CET [ Project Homepage BibTeX Download ] 338 views, 79 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo OpenNN 2.0

by Sergiointelnics - April 16, 2015, 18:38:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1831 views, 322 downloads, 3 subscriptions

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:

New utilities, correction of bugs, parallelization with OpenMP.


Logo Armadillo library 5.000

by cu24gjf - April 13, 2015, 05:05:36 CET [ Project Homepage BibTeX Download ] 55023 views, 11602 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).

Changes:
  • added spsolve() for solving sparse systems of linear equations
  • added svds() for singular value decomposition of sparse matrices
  • added nonzeros() for extracting non-zero values from matrices
  • added handling of diagonal views by sparse matrices
  • expanded repmat() to handle sparse matrices
  • expanded join_rows() and join_cols() to handle sparse matrices
  • sort_index() and stable_sort_index() have been placed in the delayed operations framework for increased efficiency
  • use of 64 bit integers is automatically enabled when using C++11
  • workaround for a bug in recent releases of Apple Xcode
  • workaround for a bug in LAPACK 3.5

Logo java machine learning platform 1.0

by openpr_nlpr - April 2, 2015, 09:02:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 633 views, 99 downloads, 2 subscriptions

About: Jmlp is a java platform for both of the machine learning experiments and application. I have tested it on the window platform. But it should be applicable in the linux platform due to the cross-platform of Java language. It contains the classical classification algorithm (Discrete AdaBoost.MH, Real AdaBoost.MH, SVM, KNN, MCE,MLP,NB) and feature reduction(KPCA,PCA,Whiten) etc.

Changes:

Initial Announcement on mloss.org.


Logo Theano 0.7

by jaberg - March 27, 2015, 16:40:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16614 views, 2981 downloads, 3 subscriptions

About: A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano.

Changes:

Theano 0.7 (26th of March, 2015)

We recommend to everyone to upgrade to this version.

Highlights:

* Integration of CuDNN for 2D convolutions and pooling on supported GPUs
* Too many optimizations and new features to count
* Various fixes and improvements to scan
* Better support for GPU on Windows
* On Mac OS X, clang is used by default
* Many crash fixes
* Some bug fixes as well

Logo libcmaes 0.9.5

by beniz - March 9, 2015, 09:05:22 CET [ Project Homepage BibTeX Download ] 4841 views, 1027 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 a major release, with several novelties, improvements and fixes, among which:

  • step-size two-point adaptaion scheme for improved performances in some settings, ref #88

  • important bug fixes to the ACM surrogate scheme, ref #57, #106

  • simple high-level workflow under Python, ref #116

  • improved performances in high dimensions, ref #97

  • improved profile likelihood and contour computations, including under geno/pheno transforms, ref #30, #31, #48

  • elitist mechanism for forcing best solutions during evolution, ref 103

  • new legacy plotting function, ref #110

  • optional initial function value, ref #100

  • improved C++ API, ref #89

  • Python bindings support with Anaconda, ref #111

  • configure script now tries to detect numpy when building Python bindings, ref #113

  • Python bindings now have embedded documentation, ref #114

  • support for Travis continuous integration, ref #122

  • lower resolution random seed initialization


Logo CN24 Convolutional Neural Networks for Semantic Segmentation 1.0

by erik - February 23, 2015, 09:02:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 863 views, 154 downloads, 1 subscription

About: CN24 is a complete semantic segmentation framework using fully convolutional networks.

Changes:

Initial Announcement on mloss.org.


Logo JMLR DLLearner 1.0

by Jens - February 13, 2015, 11:39:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16230 views, 4064 downloads, 6 subscriptions

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
(based on 3 votes)

About: The DL-Learner framework contains several algorithms for supervised concept learning in Description Logics (DLs) and OWL.

Changes:

See http://dl-learner.org/development/changelog/.


Logo Auto encoder Based Data Clustering Toolkit 1.0

by openpr_nlpr - February 10, 2015, 08:30:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 766 views, 138 downloads, 2 subscriptions

About: The auto-encoder based data clustering toolkit provides a quick start of clustering based on deep auto-encoder nets. This toolkit can cluster data in feature space with a deep nonlinear nets.

Changes:

Initial Announcement on mloss.org.


Logo JMLR Information Theoretical Estimators 0.61

by szzoli - February 8, 2015, 14:04:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 66223 views, 13745 downloads, 2 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:
  • Explicit additive constant computation in generalized kNN based Renyi entropy estimators: enhancement suggestion has been added.

  • Analytical value computation of the exponentiated Jensen-Renyi kernel-2: simplified.


Logo Somoclu 1.4.1

by peterwittek - January 28, 2015, 13:19:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7063 views, 1365 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. Apart from a command line interface, Python, R, and MATLAB are supported.

Changes:
  • Better support for ICC.
  • Faster code when compiling with GCC.
  • Building instructions and documentation improved.
  • Bug fixes: portability for R, using native R random number generator.

Logo fertilized forests 1.0beta

by Chrisl_S - January 23, 2015, 16:04:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 777 views, 175 downloads, 1 subscription

About: The fertilized forests project has the aim to provide an easy to use, easy to extend, yet fast library for decision forests. It summarizes the research in this field and provides a solid platform to extend it. Offering consistent interfaces to C++, Python and Matlab and being available for all major compilers gives the user high flexibility for using the library.

Changes:

Initial Announcement on mloss.org.


Logo Hub Miner 1.1

by nenadtomasev - January 22, 2015, 16:33:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1624 views, 294 downloads, 2 subscriptions

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

Changes:
  • BibTex support for all algorithm implementations, making all of them easy to reference (via algref package).

  • Two more hubness-aware approaches (meta-metric-learning and feature construction)

  • An implementation of Hit-Miss networks for analysis.

  • Several minor bug fixes.

  • The following instance selection methods were added: HMScore, Carving, Iterative Case Filtering, ENRBF.

  • The following clustering quality indexes were added: Folkes-Mallows, Calinski-Harabasz, PBM, G+, Tau, Point-Biserial, Hubert's statistic, McClain-Rao, C-root-k.

  • Some more experimental scripts have been included.

  • Extensions in the estimation of hubness risk.

  • Alias and weighted reservoir methods for weight-proportional random selection.


Showing Items 1-20 of 189 on page 1 of 10: 1 2 3 4 5 6 Next Last