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Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery
Non-linear dimensionality reduction Riemannian metric estimation the problem geometric discovery
2013/6/14
In recent years, manifold learning has become increasingly popular as a tool for performing non-linear dimensionality reduction. This has led to the development of numerous algorithms of varying degre...
Inverting Non-Linear Dimensionality Reduction with Scale-Free Radial Basis Interpolation
nonlinear dimensionality reduction graph Laplacian radial basis function interpolation Nyströ m method
2013/6/14
A numerical method is proposed to approximate the inverse of a general bi-Lipschitz nonlinear dimensionality reduction mapping, where the forward and consequently the inverse mappings are only explici...
A convex model for non-negative matrix factorization and dimensionality reduction on physical space
Non-negative matrix factorization dictionary learning subset selection dimensionality reduction hyperspec-tral endmember detection blind source separation
2011/3/18
A collaborative convex framework for factoring a data matrix $X$ into a non-negative product $AS$, with a sparse coefficient matrix $S$, is proposed. We restrict the columns of the dictionary matrix $...
A multivariate adaptive stochastic search method for dimensionality reduction in classification
Dimensionality reduction classification variable selection
2010/10/19
High-dimensional classification has become an increasingly important problem. In this paper we propose a "Multivariate Adaptive Stochastic Search" (MASS) approach which first reduces the dimension of...