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Dimension reduction / Nonlinear dimensionality reduction / Kernel principal component analysis / Principal component analysis / Supervised learning / Sliced inverse regression / Sufficient dimension reduction / Gaussian function / Projection / Statistics / Mathematics / Multivariate statistics


Unsupervised Kernel Dimension Reduction Meihong Wang Dept. of Computer Science U. of Southern California Los Angeles, CA 90089
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Document Date: 2011-08-01 12:49:02


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Los Angeles / Kernel / New York / /

Company

CYBY / CXY / Neural Information Processing Systems / Pearson / MIT Press / Australian & New Zealand Journal / Kendall / /

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manifold learning algorithms / estimated conditional variance operator / cross-covariance operator / conditional covariance operator / final solution / line search / trace operator / search direction / /

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National Science Foundation / American Statistical Association / Fudan University / MIT / /

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M. SvensĀ“en / max B / Michael I. Jordan / Fei Sha / J. B. Tenenbaum / V / /

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Fisher / Bishop / /

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Cauchy / /

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Kentucky / California / /

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Machine Learning / The Journal of Machine Learning Research / Journal of the American Statistical Association / /

Region

Southern California / /

Technology

giF / neural network / manifold learning algorithms / machine learning / /

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