Context Dependent Learning in Neural Networks

Spreeuwers, L.J. and Zwaag van der, B.J. and Heijden van der, F. (1995) Context Dependent Learning in Neural Networks. In: Fifth International Conference on Image Processing and its Applications, 4-6 July 1995 , Edinburgh, UK.

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Abstract:	In this paper an extension to the standard error backpropagation learning rule for multi-layer feed forward neural networks is proposed, that enables them to be trained for context dependent information. The context dependent learning is realised by using a different error function (called Average Risk: AVR) in stead of the sum of squared errors (SQE) normally used in error backpropagation and by adapting the update rules. It is shown that for applications where this context dependent information is important, a major improvement in performance is obtained.
Item Type:	Conference or Workshop Item
Copyright:	©1995 IEEE
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Signals and Systems (SAS)
Link to this item:	http://purl.utwente.nl/publications/16549
Official URL:	http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=465472
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