Software Engineering White Papers

Graph Embedding and Extensions: A General Framework for Dimensionality Reduction

Overview In graph embedding, each algorithm can be considered as the direct graph embedding or its linear/kernel/tensor extension of a specific intrinsic graph that describes certain desired statistical or geometric properties of a data set, with constraints from scale normalization or a penalty graph that characterizes a statistical or geometric property that should be avoided. Furthermore, the graph embedding framework can be used as a general platform for developing new dimensionality reduction algorithms.

Further White Paper Details
PublisherInstitute of Electrical and Electronics Engineers File FormatPDF
Date PublishedJanuary 2007
FormatWhite Papers   
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