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An algorithm for the learning of weights in discrimination functions using a priori constraints

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1 Author(s)
N. Kruger ; Inst. fur Neuroinf., Ruhr-Univ., Bochum, Germany

We introduce a learning algorithm for the weights in a very common class of discrimination functions usually called “weighted average.” The learning algorithm can reduce the number of free variables by simple but effective a priori criteria about significant features. Here we apply our algorithm to three tasks of different dimensionality all concerned with face recognition

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:19 ,  Issue: 7 )