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Subspace manifold learning with sample weights
2009
Image and Vision Computing
Subspace manifold learning represents a popular class of techniques in statistical image analysis and object recognition. Recent research in the field has focused on nonlinear representations; locally linear embedding (LLE) is one such technique that has recently gained popularity. We present and apply a generalization of LLE that introduces sample weights. We demonstrate the application of the technique to face recognition, where a model exists to describe each face's probability of
doi:10.1016/j.imavis.2006.10.007
fatcat:vf2lgklcivaqxn4kelcnfivq4e