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Logo JMLR GPML Gaussian Processes for Machine Learning Toolbox 4.0

by hn - October 19, 2016, 10:15:05 CET [ Project Homepage BibTeX Download ] 38881 views, 8726 downloads, 5 subscriptions

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About: The GPML toolbox is a flexible and generic Octave/Matlab implementation of inference and prediction with Gaussian process models. The toolbox offers exact inference, approximate inference for non-Gaussian likelihoods (Laplace's Method, Expectation Propagation, Variational Bayes) as well for large datasets (FITC, VFE, KISS-GP). A wide range of covariance, likelihood, mean and hyperprior functions allows to create very complex GP models.

Changes:

A major code restructuring effort did take place in the current release unifying certain inference functions and allowing more flexibility in covariance function composition. We also redesigned the whole derivative computation pipeline to strongly improve the overall runtime. We finally include grid-based covariance approximations natively.

More generic sparse approximation using Power EP

  • unified treatment of FITC approximation, variational approaches VFE and hybrids

  • inducing input optimisation for all (compositions of) covariance functions dropping the previous limitation to a few standard examples

  • infFITC is now covered by the more generic infGaussLik function

Approximate covariance object unifying sparse approximations, grid-based approximations and exact covariance computations

  • implementation in cov/apx, cov/apxGrid, cov/apxSparse

  • generic infGaussLik unifies infExact, infFITC and infGrid

  • generic infLaplace unifies infLaplace, infFITC_Laplace and infGrid_Laplace

Hiearchical structure of covariance functions

  • clear hierachical compositional implementation

  • no more code duplication as present in covSEiso and covSEard pairs

  • two mother covariance functions

    • covDot for dot-product-based covariances and

    • covMaha for Mahalanobis-distance-based covariances

  • a variety of modifiers: eye, iso, ard, proj, fact, vlen

  • more flexibility as more variants are available and possible

  • all covariance functions offer derivatives w.r.t. inputs

Faster derivative computations for mean and cov functions

  • switched from partial derivatives to directional derivatives

  • simpler and more concise interface of mean and cov functions

  • much faster marginal likelihood derivative computations

  • simpler and more compact code

New mean functions

  • new mean/meanWSPC (Weighted Sum of Projected Cosines or Random Kitchen Sink features) following a suggestion by William Herlands

  • new mean/meanWarp for constructing a new mean from an existing one by means of a warping function adapted from William Herlands

New optimizer

  • added a new minimize_minfunc, contributed by Truong X. Nghiem

New GLM link function

  • added the twice logistic link function util/glm_invlink_logistic2

Smaller fixes

  • two-fold speedup of util/elsympol used by covADD by Truong X. Nghiem

  • bugfix in util/logphi as reported by John Darby


Logo JMLR GPstuff 4.7

by avehtari - June 9, 2016, 17:45:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 38353 views, 9252 downloads, 3 subscriptions

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About: The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods.

Changes:

2016-06-09 Version 4.7

Development and release branches available at https://github.com/gpstuff-dev/gpstuff

New features

  • Simple Bayesian Optimization demo

Improvements

  • Improved use of PSIS
  • More options added to gp_monotonic
  • Monotonicity now works for additive covariance functions with selected variables
  • Possibility to use gpcf_squared.m-covariance function with derivative observations/monotonicity
  • Default behaviour made more robust by changing default jitter from 1e-9 to 1e-6
  • LA-LOO uses the cavity method as the default (see Vehtari et al (2016). Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models. JMLR, accpeted for publication)
  • Selected variables -option works now better with monotonicity

Bugfixes

  • small error in derivative observation computation fixed
  • several minor bug fixes

Logo FEAST 1.1.4

by apocock - March 12, 2016, 18:35:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 39341 views, 7108 downloads, 2 subscriptions

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About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:
  • Fixed an issue where zero MI values would cause it to segfault.
  • Fixes to documentation and comments.
  • Updated internal version of MIToolbox.

Logo JMLR libDAI 0.3.2

by jorism - July 17, 2015, 15:59:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 53189 views, 9907 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.


Logo TMBP 1.0

by zengjia - April 5, 2012, 06:42:26 CET [ BibTeX BibTeX for corresponding Paper Download ] 7948 views, 4232 downloads, 2 subscriptions

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About: Message passing for topic modeling

Changes:
  1. improve "readme.pdf".
  2. correct some compilation errors.

Logo LSTM for biological sequence analysis 1.0

by mhex - July 28, 2010, 16:32:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8716 views, 2087 downloads, 1 subscription

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About: Implementation of LSTM for biological sequence analysis (classification, regression, motif discovery, remote homology detection). Additionally a LSTM as logistic regression with spectrum kernel is included.

Changes:

Spectrum LSTM package included


Logo HSSVM 1.0.1

by xjbean - June 8, 2010, 16:16:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14203 views, 2859 downloads, 1 subscription

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About: HSSVM is a software for solving multi-class problem using Hyper-sphere Support Vector Machines model, implemented by Java.

Changes:
  1. From this version, the version number is normalized to hssvm1.0.1;
  2. In this version, we delete the features about running parameter searching and run-all from Ant script, that is, commands "ant search-param" and "ant run-all" which exist in previous version are no longer available, and they are replaced with commands "svm search conf" and "svm runall conf", both of them are used on Linux(or all other POSIX systems).If you want to use this program on Windows, the cygwin is required to be installed.

Logo SimpleMKL 0.5

by arakotom - June 11, 2008, 00:56:47 CET [ Project Homepage BibTeX Download ] 12953 views, 3422 downloads, 5 subscriptions

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About: Matlab Multiple Kernel Learning toolbox. Features : MKL for SVM Classification, Regression and MultiClass. It needs SVM-KM Toolbox

Changes:

Initial Announcement on mloss.org.


Logo RapidMiner 4.0

by ingomierswa - November 16, 2007, 02:31:48 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 20127 views, 3480 downloads, 0 comments, 0 subscriptions

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About: RapidMiner (formerly YALE) is one of the most widely used open-source data mining suites and software solutions due to its leading-edge technologies and its functional range. Applications of [...]

Changes:

Initial Announcement on mloss.org.


Logo r-cran-e1071 1.6-7

by r-cran-robot - December 1, 2016, 00:00:05 CET [ Project Homepage BibTeX Download ] 32030 views, 6442 downloads, 3 subscriptions

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About: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly

Changes:

Fetched by r-cran-robot on 2016-12-01 00:00:05.332167


Showing Items 1-10 of 628 on page 1 of 63: 1 2 3 4 5 6 Next Last