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» Non-Linear Dimensionality Reduction
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UAI
2000
15 years 5 months ago
Experiments with Random Projection
Recent theoretical work has identified random projection as a promising dimensionality reduction technique for learning mixtures of Gaussians. Here we summarize these results and ...
Sanjoy Dasgupta
BIOWIRE
2007
Springer
15 years 10 months ago
Beta Random Projection
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. In particular, r...
Yu-En Lu, Pietro Liò, Steven Hand
JMLR
2010
155views more  JMLR 2010»
14 years 11 months ago
Bayesian Gaussian Process Latent Variable Model
We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensionality reduction. This method...
Michalis Titsias, Neil D. Lawrence
165
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NIPS
2001
15 years 5 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi
NIPS
2003
15 years 5 months ago
Optimal Manifold Representation of Data: An Information Theoretic Approach
We introduce an information theoretic method for nonparametric, nonlinear dimensionality reduction, based on the infinite cluster limit of rate distortion theory. By constraining...
Denis V. Chigirev, William Bialek