Network Structuring and Training Using Rule-based Knowledge

Tresp, Volker, Hollatz, Jürgen, Ahmad, Subutai

Neural Information Processing Systems 

We demonstrate in this paper how certain forms of rule-based knowledge can be used to prestructure a neural network of normalized basis functions and give a probabilistic interpretation of the network architecture.

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