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    CLASSIFICATION
    2006
    108views more  CLASSIFICATION 2006»
    The Practice of Cluster Analysis
    13 years 4 months ago
    The Practice of Cluster Analysis
    Download  www.interfacesymposia.org
    Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
    Jon R. Kettenring
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    DM
    2006
    128views more  DM 2006»
    Non-trivial t-designs without repeated blocks exist for all t
    13 years 4 months ago
    Non-trivial t-designs without repeated blocks exist for all t
    Download  did.mat.uni-bayreuth.de
    A computer package is being developed at Bayreuth for the generation and investigation of discrete structures. The package is a C and C++ class library of powerful algorithms endow...
    Luc Teirlinck
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    FGCS
    2006
    144views more  FGCS 2006»
    BioSimGrid: Grid-enabled biomolecular simulation data storage and analysis
    13 years 4 months ago
    BioSimGrid: Grid-enabled biomolecular simulation data storage and analysis
    Download  eprints.soton.ac.uk
    In computational biomolecular research, large amounts of simulation data are generated to capture the motion of proteins. These massive simulation data can be analysed in a number...
    Muan Hong Ng, Steven Johnston, Bing Wu, Stuart E. ...
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    PR
    2006
    164views more  PR 2006»
    Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
    13 years 4 months ago
    Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
    Download  repository.ust.hk
    Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
    Hong Chang, Dit-Yan Yeung
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    PAMI
    2002
    114views more  PAMI 2002»
    Principal Manifolds and Probabilistic Subspaces for Visual Recognition
    13 years 4 months ago
    Principal Manifolds and Probabilistic Subspaces for Visual Recognition
    Download  www.merl.com
    We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
    Baback Moghaddam
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