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Parity still isn't a generalisation problem

Published online by Cambridge University Press:  01 April 1998

R. I. Damper
Affiliation:
Cognitive Sciences Centre and Department of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, Englandrid@ecs.soton.ac.uk http://isis.ecs.soton.ac.uk/

Abstract

Clark & Thornton take issue with my claim that parity is not a generalisation problem, and that nothing can be inferred about back-propagation in particular, or learning in general, from failures of parity generalisation. They advance arguments to support their contention that generalisation is a relevant issue. In this continuing commentary, I examine generalisation more closely in order to refute these arguments. Different learning algorithms will have different patterns of failure: back-propagation has no special status in this respect. This is not to deny that a particular algorithm might fortuitously happen to produce the “intended” function in an (oxymoronic) parity-generalisation task.

Type
Continuing Commentary
Copyright
© 1998 Cambridge University Press

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