Welcome to VBSR toolbox web page
What is VBSR toolbox?
In this Variational Bayesian Sparse Regression toolbox (VBSR toolbox hereafter), we implemented several sparse regression algorithms based on Variational Bayesian (VB) method with ARD (Automatic Relevance Determination) prior. In order to apply time series data, we also implemented time embedding representation for output prediction from input time series. Our main concern in this toolbox is to implement efficient methods which can deal with very high input dimension over 10,000.
Implemented algorithms
How to use
Please see Usage-predict.txt and testjob.m for more detail on how to use this toolbox.
Time delay embedding
Please see Read_embed.txt for time delay embedding representation. In the previous version, time delay embedding was done before estimation. When input dimension becomes very large, this requires huge amount of memory and time. Therefore, embedding was done inside the estimation program using MEX-program.
Introduction of sparse estimation

Sato M., (2001). On-line model selection based on the variational Bayes. Neural Computation, 13, 1649-1681.

Toda, A., Imamizu, H., Sato, M., Wada, Y., Kawato, M., (2007). Reconstruction of temporal movement from single-trial non-invasive brain activity: A hierarchical Bayesian method. The 14th International Conference on Neural Information Processing (ICONIP2007).

Isao Nambu, Rieko Osu, Masa-aki Sato, Soichi Ando, Mitsuo Kawato, Eiichi Naito, (2009). Single-trial reconstruction of finger-pinch forces from human motor-cortical activation measured by near-infrared spectroscopy (NIRS) NeuroImage 47, 628-637.

Tipping, M. E. and A. C. Faul, (2003). Fast marginal likelihood maximisation for sparse Bayesian models. In C. M. Bishop and B. J. Frey (Eds.), Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, Key West, FL, Jan 3-6.

The codes in the toolbox were written for MATLAB ver.6.5 or later.
VBSR toolbox is free but copyright software, distributed under the terms of the GNU General Public License as published by the Free Software Foundation . Further details on GPL can be found at No formal support or maintenance is provided or implied.
Masa-aki Sato
ATR Computational Neuroscience Laboratories
Department of Computational Brain Imaging