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