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    AAAI
    2006
    112views Intelligent Agents» more  AAAI 2006»
    An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding
    13 years 6 months ago
    An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding
    Download  cseweb.ucsd.edu
    Kilian Q. Weinberger, Lawrence K. Saul
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    ICML
    2006
    IEEE
    147views Machine Learning» more  ICML 2006»
    A duality view of spectral methods for dimensionality reduction
    14 years 5 months ago
    A duality view of spectral methods for dimensionality reduction
    Download  www.stanford.edu
    We present a unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenm...
    Lin Xiao, Jun Sun 0003, Stephen P. Boyd
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    NIPS
    2007
    123views Information Technology» more  NIPS 2007»
    Colored Maximum Variance Unfolding
    13 years 6 months ago
    Colored Maximum Variance Unfolding
    Download  books.nips.cc
    Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
    Le Song, Alex J. Smola, Karsten M. Borgwardt, Arth...
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    ICML
    2004
    IEEE
    189views Machine Learning» more  ICML 2004»
    Learning a kernel matrix for nonlinear dimensionality reduction
    13 years 10 months ago
    Learning a kernel matrix for nonlinear dimensionality reduction
    Download  www-rcf.usc.edu
    We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
    Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
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    BMCBI
    2010
    243views more  BMCBI 2010»
    Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
    13 years 5 months ago
    Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
    Download  www.biomedcentral.com
    Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
    Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
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