Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction

IEEE-Inst Electrical Electronics Engineers Inc
Publication Type:
Journal Article
IEEE Transactions On Systems Man And Cybernetics Part B-Cybernetics, 2011, 41 (2), pp. 425 - 434
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The Gaussian process latent variable model (GP-LVM) has been identified to be an effective probabilistic approach for dimensionality reduction because it can obtain a low-dimensional manifold of a data set in an unsupervised fashion. Consequently, the GP
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