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Abstract: Eigen decomposition is a central mathematical tool in many pattern recognition and machine learning techniques. However, it becomes computationally infeasible in the presence of a large set of high-dimensional samples. Moreover, in highly dynamic domains with a continual supply of new samples, an incremental approach that keeps on updating the eigen decomposition will be more desirable than the traditional approach of simply re-computing the decomposition from scratch. In this paper, by using a ... (Update)
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BibTeX entry: (Update)
@misc{ and-incremental,
author = "James Kwok And",
title = "Incremental Eigen Decomposition",
url = "citeseer.ist.psu.edu/610624.html" }
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