Goto

Collaborating Authors

 Heading, Anthony J. R.


Unsupervised Classifiers, Mutual Information and 'Phantom Targets

Neural Information Processing Systems

We derive criteria for training adaptive classifier networks to perform unsupervised data analysis. The first criterion turns a simple Gaussian classifier into a simple Gaussian mixture analyser. The second criterion, which is much more generally applicable, is based on mutual information.


Unsupervised Classifiers, Mutual Information and 'Phantom Targets

Neural Information Processing Systems

We derive criteria for training adaptive classifier networks to perform unsupervised data analysis. The first criterion turns a simple Gaussian classifier into a simple Gaussian mixture analyser. The second criterion, which is much more generally applicable, is based on mutual information.


Unsupervised Classifiers, Mutual Information and 'Phantom Targets

Neural Information Processing Systems

We derive criteria for training adaptive classifier networks to perform unsupervised dataanalysis. The first criterion turns a simple Gaussian classifier into a simple Gaussian mixture analyser. The second criterion, which is much more generally applicable, is based on mutual information.