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lec7 (1) - Nonlinear Dimensionality Reduction Science 22...

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Lecture 7: Unsupervised Learning Techniques Andrea Caponnetto Description To introduce some methods for unsupervised learning: Gaussian Mixtures, K-Means, ISOMAP, HLLE, Laplacian Eigenmaps. Suggested Reading Hastie, Tibshirani, Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer 2001. Tenenbaum, de Silva, Langford. A Global Geometric Framework for
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Unformatted text preview: Nonlinear Dimensionality Reduction. Science 22 December 2000; Vol. 290. no. 5500, pp. 2319 - 2323. • Donoho, Grimes. Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data. 2003. • M. Belkin, P. Niyogi. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation. Neural Computation, June 2003; 15 (6):1373-1396....
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