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    » Semi-supervised nonlinear dimensionality reduction
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    IJON
    2006
    85views more  IJON 2006»
    From outliers to prototypes: Ordering data
    13 years 8 months ago
    From outliers to prototypes: Ordering data
    Download  www.kyb.tuebingen.mpg.de
    We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show ...
    Stefan Harmeling, Guido Dornhege, David M. J. Tax,...
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    CIKM
    2008
    Springer
    148views Information Technology» more  CIKM 2008»
    REDUS: finding reducible subspaces in high dimensional data
    13 years 10 months ago
    REDUS: finding reducible subspaces in high dimensional data
    Download  www.cs.unc.edu
    Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
    Xiang Zhang, Feng Pan, Wei Wang 0010
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    JMLR
    2010
    186views more  JMLR 2010»
    Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
    13 years 3 months ago
    Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
    Download  jmlr.csail.mit.edu
    We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
    Philippos Mordohai, Gérard G. Medioni
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    PR
    2007
    145views more  PR 2007»
    Face recognition using a kernel fractional-step discriminant analysis algorithm
    13 years 8 months ago
    Face recognition using a kernel fractional-step discriminant analysis algorithm
    Download  www.cs.ust.hk
    Feature extraction is among the most important problems in face recognition systems. In this paper, we propose an enhanced kernel discriminant analysis (KDA) algorithm called kern...
    Guang Dai, Dit-Yan Yeung, Yuntao Qian
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    BMCBI
    2005
    80views more  BMCBI 2005»
    Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
    13 years 8 months ago
    Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
    Download  www.biomedcentral.com
    Background: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently ...
    Kevin Dawson, Raymond L. Rodriguez, Wasyl Malyj
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