Project details for The Generalised Linear Models Inference and Estimation Toolbox

Logo JMLR The Generalised Linear Models Inference and Estimation Toolbox 1.5

by hn - November 8, 2013, 13:58:03 CET [ Project Homepage BibTeX Download ]

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Description:

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 to previous version:

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

BibTeX Entry: Download
URL: Project Homepage
JMLR MLOSS PaperURL: JMLR-MLOSS Paper Homepage
Supported Operating Systems: Agnostic, Platform Independent
Data Formats: Matlab, Octave
Tags: Approximate Inference, Sparse Learning, Logistic Regression
Archive: download here

Other available revisons

Version Changelog Date
1.5

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

August 31, 2013, 22:38:05
1.4

contributed by George Papandreou:

  • preconditioning support in the inf/linsolve_lcg.m CG routine.

  • @matConv2 and @matFD2 support different boundary conditions in deblurring

  • various mat/@*/diagFAtAFt.m support circulant preconditioning

  • bugfixes in nonnegativity option in pls/plsLBFGS.m and pen/penVBNorm.m when used together with EP

  • inf/diag_inv_sample.m, a Monte Carlo estimator

gfortran support to pls/lbfgsb/Makefile (thanks to Ernst Kloppenburg)

slight modification to mat/@matFFTN/mvm.m to make it more consistent

simple gradient solver using Barzilai-Borwein step size pls/plsBB.m

October 19, 2011, 22:26:05
1.3

extension of the matrix class; bugfixes

plsSB - split Bregmin PLS solver

new inference engine dli.m instead of vbidl.m

  • support of parallel EP in addition to VB

  • marginal likelihood computation

extended documentation and demo programs

November 12, 2010, 09:57:36
1.2

New matrix class

Bugfixes

More examples

New penalty and potential functions

Group sparsity support

August 27, 2010, 11:27:27
1.1

Added demo examples and documentation.

August 10, 2010, 09:05:48
1.0

Initial Announcement on mloss.org.

August 10, 2010, 08:48:20
v1.0

Initial Announcement on mloss.org.

August 10, 2010, 08:29:47

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