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Showing Items 61-70 of 519 on page 7 of 52: First Previous 2 3 4 5 6 7 8 9 10 11 12 Next Last

Logo JMLR Waffles 2013-12-09

by mgashler - December 9, 2013, 18:04:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 20418 views, 6354 downloads, 1 subscription

About: Script-friendly command-line tools for machine learning and data mining tasks. (The command-line tools wrap functionality from a public domain C++ class library.)

Changes:

Changed the license from LGPL to CC0. Added classes for stackable autoencoders and restricted boltzmann machines. Polished up the GBayesianNetwork class and add examples and unit tests. Added support for CMake. Made the build process also support clang, and be more mac-friendly. Simplified some important classes, including GMatrix and GNeuralNet. Enforced const correctness in more places. Nixed most uses of smart pointers. Made all learning algorithms thread-safe. Added thread-parallelism to several ensemble methods. Added support for binary division trees. Added some common activation functions. Added a tool to generate a vector of meta statistics about a dataset. Added several small-but-useful tools. Simplified the docs and web site.


Logo StirlingNumbers 1.0

by stefanwebb - December 9, 2013, 03:26:56 CET [ Project Homepage BibTeX Download ] 484 views, 119 downloads, 1 subscription

About: A library for calculating and accessing generalized Stirling numbers of the second kind, which are used for inference in Poisson-Dirichlet processes.

Changes:

Initial Announcement on mloss.org.


Logo Theano 0.6

by jaberg - December 3, 2013, 20:32:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11315 views, 2138 downloads, 1 subscription

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 0.6 (December 3th, 2013)

Highlight:

* Last release with support for Python 2.4 and 2.5.
* We will try to release more frequently.
* Fix crash/installation problems.
* Use less memory for conv3d2d.

0.6rc4 skipped for a technical reason.

Highlights (since 0.6rc3):

* Python 3.3 compatibility with buildbot test for it.
* Full advanced indexing support.
* Better Windows 64 bit support.
* New profiler.
* Better error messages that help debugging.
* Better support for newer NumPy versions (remove useless warning/crash).
* Faster optimization/compilation for big graph.
* Move in Theano the Conv3d2d implementation.
* Better SymPy/Theano bridge: Make an Theano op from SymPy expression and use SymPy c code generator.
* Bug fixes.

Too much changes in 0.6rc1, 0.6rc2 and 0.6rc3 to list here. See https://github.com/Theano/Theano/blob/master/NEWS.txt for details.


Logo Jubatus 0.5.0

by hido - November 30, 2013, 17:41:50 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1408 views, 233 downloads, 1 subscription

About: Jubatus is a general framework library for online and distributed machine learning. It currently supports classification, regression, clustering, recommendation, nearest neighbors, anomaly detection, and graph analysis. Loose model sharing provides higher scalability, better performance, and real-time capabilities, by combining online learning with distributed computations.

Changes:

0.5.0 add new supports for clustering and nearest neighbors. For more detail, see http://t.co/flMcTcYZVs


Logo hca 0.41

by wbuntine - November 29, 2013, 03:16:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1576 views, 256 downloads, 2 subscriptions

About: Non-parametric 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:

Added example on using burstiness.


Logo r-cran-evtree 0.1-4

by r-cran-robot - November 25, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 2440 views, 502 downloads, 0 subscriptions

About: Evolutionary Learning of Globally Optimal Trees

Changes:

Fetched by r-cran-robot on 2014-04-01 00:00:04.866198


Logo GBAC 0.0.4

by henrydcl - November 22, 2013, 20:04:16 CET [ BibTeX BibTeX for corresponding Paper Download ] 1575 views, 553 downloads, 2 subscriptions

About: Probabilistic performance evaluation for multiclass classification using the posterior balanced accuracy

Changes:

Added bibtex information.


Logo Bayesian Model Averaging Library 0.3

by duric1 - November 16, 2013, 04:42:05 CET [ Project Homepage BibTeX Download ] 572 views, 122 downloads, 1 subscription

About: Bayesian Model Averaging for linear models with a wide choice of (customizable) priors. Built-in priorss include coefficient priors (fixed, flexible and hyper-g priors), 5 kinds of model priors, moreover model sampling by enumeration or various MCMC approaches.

Changes:

Initial Announcement on mloss.org.


  • Authors: Duric
  • License: Gnu
  • Programming Language: R

Logo JMLR GPML Gaussian Processes for Machine Learning Toolbox 3.4

by hn - November 11, 2013, 14:46:52 CET [ Project Homepage BibTeX Download ] 14753 views, 3895 downloads, 3 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarWhole Star
(based on 2 votes)

About: The GPML toolbox is a flexible and generic Octave 3.2.x and Matlab 7.x implementation of inference and prediction in Gaussian Process (GP) models.

Changes:
  • derivatives w.r.t. inducing points xu in infFITC, infFITC_Laplace, infFITC_EP so that one can treat the inducing points either as fixed given quantities or as additional hyperparameters
  • new GLM likelihood likExp for inter-arrival time modeling
  • new GLM likelihood likWeibull for extremal value regression
  • new GLM likelihood likGumbel for extremal value regression
  • new mean function meanPoly depending polynomially on the data
  • infExact can deal safely with the zero noise variance limit
  • support of GP warping through the new likelihood function likGaussWarp

About: The glm-ie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glm-ie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some MEX files. The code is fully compatible to both Matlab 7.x and GNU Octave 3.2.x. Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework allowing for both MAP estimation and approximate Bayesian inference.

Changes:

added factorial mean field inference as a third algorithm complementing expectation propagation and variational Bayes

generalised non-Gaussian potentials so that affine instead of linear functions of the latent variables can be used


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