Next: Introduction
Harri Valpola, Tapani Raiko and Juha Karhunen1
Building Blocks for Hierarchical Latent Variable Models
Date: October 1, 2001
Helsinki University of Technology, Neural Networks Research Centre
P.O.Box 5400, FIN-02015 HUT, Espoo, Finland
E-mail: {Harri.Valpola, Tapani.Raiko, Juha.Karhunen}@hut.fi
URL: http://www.cis.hut.fi/projects/ica/bayes/
Abstract:
We introduce building blocks from which a large variety of latent
variable models can be built. The blocks include continuous and
discrete variables, summation, addition, nonlinearity and switching.
Ensemble learning provides a cost function which can be used for
updating the variables as well as optimising the model structure.
The blocks are designed to fit together and to yield efficient
update rules. Emphasis is on local computation which results in
linear computational complexity. We propose and test a structure
with a hierachical nonlinear model for variances and means.
Harri Valpola
2001-10-01