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    ISCI
    2006
    45views more  ISCI 2006»
    A scalable supervised algorithm for dimensionality reduction on streaming data
    13 years 4 months ago
    A scalable supervised algorithm for dimensionality reduction on streaming data
    Download  www.cs.ust.hk
    Jun Yan, Benyu Zhang, Shuicheng Yan, Ning Liu, Qia...
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    NIPS
    2008
    194views Information Technology» more  NIPS 2008»
    Supervised Exponential Family Principal Component Analysis via Convex Optimization
    13 years 6 months ago
    Supervised Exponential Family Principal Component Analysis via Convex Optimization
    Download  www.cis.temple.edu
    Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
    Yuhong Guo
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    EPIA
    2003
    Springer
    112views Artificial Intelligence» more  EPIA 2003»
    Mining Low Dimensionality Data Streams of Continuous Attributes
    13 years 10 months ago
    Mining Low Dimensionality Data Streams of Continuous Attributes
    Download  www.upo.es
    This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
    Francisco J. Ferrer-Troyano, Jesús S. Aguil...
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    SDM
    2007
    SIAM
    108views Data Mining» more  SDM 2007»
    Semi-Supervised Dimensionality Reduction
    13 years 6 months ago
    Semi-Supervised Dimensionality Reduction
    Download  cs.nju.edu.cn
    Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
    Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
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    ICML
    2005
    IEEE
    165views Machine Learning» more  ICML 2005»
    Supervised dimensionality reduction using mixture models
    14 years 5 months ago
    Supervised dimensionality reduction using mixture models
    Download  talk.ucsd.edu
    Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
    Sajama, Alon Orlitsky
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