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Dimensionality reduction is a problem of fundamental importance in both machine learning and data mining. In this paper, we develop a new approach that can process labeled datasets and accurately reduce their dimensionalities. The approach is based on a new objective that contains information from both the global and local structures of a data set. An iterative approach is used to compute the directions...
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