Validation and Verification of Neural Network Systems
The time scale of the project is as follows:
During the first year we have implemented a
Bayesian training of neural networks
to classify outdoors images.
Within this framework we have also addressed the issue of error bars
on prediction and feature selection.
The final part of this research concerns more theoretical issues.
In particular we investigate the issue of generalisation
from a theoretical point of view, trying to understand how
generalisation is affected by the amount of training data.
The study of the issue of dimensionality reduction
using latent variables has already started.