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    » Learning to Classify Texts Using Positive and Unlabeled Data
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    MLDM
    2007
    Springer
    120views Machine Learning» more  MLDM 2007»
    Transductive Learning from Relational Data
    14 years 1 months ago
    Transductive Learning from Relational Data
    Download  www.cs.uu.nl
    Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
    Michelangelo Ceci, Annalisa Appice, Nicola Barile,...
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    IGARSS
    2009
    171views Remote Sensing» more  IGARSS 2009»
    Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs
    13 years 5 months ago
    Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs
    Download  ideal.ece.utexas.edu
    Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
    Alexander Liu, Goo Jun, Joydeep Ghosh
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    TKDE
    2008
    111views more  TKDE 2008»
    Text Clustering with Feature Selection by Using Statistical Data
    13 years 7 months ago
    Text Clustering with Feature Selection by Using Statistical Data
    Download  dblab.mgt.ncu.edu.tw
    Abstract-- Feature selection is an important method for improving the efficiency and accuracy of text categorization algorithms by removing redundant and irrelevant terms from the ...
    Yanjun Li, Congnan Luo, Soon M. Chung
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    CVPR
    2006
    IEEE
    257views Computer Vision» more  CVPR 2006»
    Unsupervised Learning of Categories from Sets of Partially Matching Image Features
    14 years 9 months ago
    Unsupervised Learning of Categories from Sets of Partially Matching Image Features
    Download  vision.jhu.edu
    We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
    Kristen Grauman, Trevor Darrell
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    NIPS
    2008
    211views Information Technology» more  NIPS 2008»
    Multi-Level Active Prediction of Useful Image Annotations for Recognition
    13 years 9 months ago
    Multi-Level Active Prediction of Useful Image Annotations for Recognition
    Download  www.cs.utexas.edu
    We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...
    Sudheendra Vijayanarasimhan, Kristen Grauman
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