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Titlebook: Artificial Neural Networks - ICANN 96; 6th International Co Christoph Malsburg,Werner Seelen,Bernhard Sendhoff Conference proceedings 1996

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Artificial Neural Networks - ICANN 96978-3-540-68684-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Measuring Areas of Rectangular Fields,r, so far there existed no way of adding knowledge about invariances of a classification problem at hand. We present a method of incorporating prior knowledge about transformation invariances by applying transformations to support vectors, the training examples most critical for determining the classification boundary.
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Measuring Areas of Rectangular Fields,ace. We specify an algorithm to generate representative weight vectors in a specific fundamental domain. The analysis of the metric structure of the fundamental domain enables us to use the . information of weight vector estimates, e. g. for cluster analysis. This can be implemented efficiently even for large networks.
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Dividing Fields Among Partners,ask shows a tendency to strong overfitting on the other hand its optimal training scheme is known. In the regime, where overfitting occurs, on-line training outperforms batch training quite easily. Asymptotically, off-line training is better but if the learning rate is chosen carefully on-line training remains competitive.
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