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An Algorithm for the Learning of Weights in Discrimination Functions Using a Priori Constraints
July 1997 (vol. 19 no. 7)
pp. 764-768

Abstract—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.

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Index Terms:
Discrimination functions, a priori knowledge, weighting, face recognition, elastic graph matching.
Citation:
Norbert Krüger, "An Algorithm for the Learning of Weights in Discrimination Functions Using a Priori Constraints," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 764-768, July 1997, doi:10.1109/34.598233
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