Adaptive Mixtures of Local Experts
Robert Jacobs, Michael Jordan
Department of Brain and Cognitive Sciences
MIT, Cambridge, MA, USA
Steven Nowlan, Geoffrey Hinton
Department of Computer Science
University of Toronto & University of Toronto
We present a new supervised learning procedure for systems composed
of many separate networks, each of which learns to handle a subset of the complete set of
training cases. The new procedure can be viewed either as a modular version of a
multilayer supervised networks, or as an associative version of competitive learning.
It therefore provides a new link between these two apparently different approaches.
We demonstrate that the learning procedure divides up a vowel discrimination task
into appropriate subtasks, each of which can be solved by a very simple expert network.
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