GLLiM: a flexible Matlab toolbox for Gaussian Locally Linear Mapping

The GLLiM toolbox v1.0 provides a set of Matlab functions allowing to learn a relationship between two spaces.
It implements the  hGLLiM algorithm described in detail in: A. Deleforge, F. Forbes, and R. Horaud. High-Dimensional Regression with Gaussian Mixtures and Partially-Latent Response Variables. Statistics and Computing. 2014. The article is available online on arXiv at

This is GLLiM v1.0 as described in the original paper. New versions of GLLiM are currently under development at the following GitHub:
An R package for GLLiM as well as its extensions SLLiM and BLLiM is also downloadable at

The toolbox also contains an example of application (EXAMPLE.m) using the freely available Stanford dataset for faces:

Download the toolbox v1.0

GLLiM v1.0 is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
GLLiM v1.0 is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with GLLiM v1.0. If not, see

For any questions regarding the toolbox, please contact Antoine Deleforge.


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