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 http://arxiv.org/abs/1308.2302.
This is GLLiM v1.0 as described in the original paper. New versions of GLLiM are currently under development at the following GitHub: https://github.com/Chutlhu/GLLiM.An R package for GLLiM as well as its extensions SLLiM and BLLiM is also downloadable at https://cran.r-project.org/web/packages/xLLiM/index.html
The toolbox also contains an example of application (EXAMPLE.m) using the freely available Stanford dataset for faces: http://isomap.stanford.edu/datasets.html.
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 https://www.gnu.org/licenses
For any questions regarding the toolbox, please contact Antoine Deleforge.
