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Abstract: Linear discriminant analysis is a popular technique in computer vision, machine learning and data mining. It has been successfully applied to various problems, and there are numerous variations of the original approach. This paper introduces the idea of separable LDA. Towards the problem of binary classification for visual object recognition, we derive an algorithm for training separable discriminant classifiers. Our approach provides rapid training and runtime behavior and also tackles... (Update)
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BibTeX entry: (Update)
@misc{ and-separable,
author = "Christian Bauckhage And",
title = "Separable Linear Discriminant Classification",
url = "citeseer.ist.psu.edu/738743.html" }
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