glm-ie: The Generalised Linear Models Inference and Estimation Toolbox

2012

Article

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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 The code is fully compatible to both Matlab 7.x and GNU Octave 3.3.x. Abstract Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework.

Author(s): Nickisch, H.
Journal: Journal of Machine Learning Research
Volume: 13
Pages: 1699-1703
Year: 2012
Month: May
Day: 0

Department(s): Empirical Inference
Research Project(s): Probabilistic Inference
Bibtex Type: Article (article)

Digital: 0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@article{6939,
  title = {glm-ie: The Generalised Linear Models Inference and Estimation Toolbox},
  author = {Nickisch, H.},
  journal = {Journal of Machine Learning Research},
  volume = {13},
  pages = {1699-1703},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = may,
  year = {2012},
  month_numeric = {5}
}