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Nonlinear Dimensionality Reduction as Information Retrieval
Journal of machine learning research
Nonlinear dimensionality reduction has so far been treated either as a data representation problem or as a search for a lowerdimensional manifold embedded in the data space. A main application for both is in information visualization, to make visible the neighborhood or proximity relationships in the data, but neither approach has been designed to optimize this task. We give such visualization a new conceptualization as an information retrieval problem; a projection is good if neighbors of datadblp:journals/jmlr/VennaK07 fatcat:s6xxeqktzngibn6ficktjq7i4a