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Recently, there are several algorithms to perform dimensionality reduction on low-dimensional nonlinear manifolds embedded in a high-dimensional space, such as ISOMAP, LLE, Laplacian eigenmaps, SPE and so on. Most of these techniques work in batch mode. In this paper, we present an incremental nonlinear dimensionality reduction algorithm based on the k nearest neighbor projection. The method can effectively...
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