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    CVPR
    2003
    IEEE
    219views Computer Vision» more  CVPR 2003»
    Kernel Principal Angles for Classification Machines with Applications to Image Sequence Interpretation
    15 years 12 months ago
    Kernel Principal Angles for Classification Machines with Applications to Image Sequence Interpretation
    Download  www.cs.huji.ac.il
    We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A B) defined over pairs of matrices A B base...
    Lior Wolf, Amnon Shashua
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    ICML
    2009
    IEEE
    134views Machine Learning» more  ICML 2009»
    Learning Markov logic network structure via hypergraph lifting
    15 years 10 months ago
    Learning Markov logic network structure via hypergraph lifting
    Download  www.cs.washington.edu
    Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
    Stanley Kok, Pedro Domingos
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    ECML
    2006
    Springer
    221views Machine Learning» more  ECML 2006»
    Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
    15 years 1 months ago
    Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
    Download  sci2s.ugr.es
    Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
    Corneliu Henegar, Karine Clément, Jean-Dani...
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    ICML
    2009
    IEEE
    150views Machine Learning» more  ICML 2009»
    Boosting with structural sparsity
    15 years 10 months ago
    Boosting with structural sparsity
    Download  www.cs.berkeley.edu
    Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
    John Duchi, Yoram Singer
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    CVPR
    2009
    IEEE
    352views Computer Vision» more  CVPR 2009»
    Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
    16 years 5 months ago
    Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
    Download  www.kyb.mpg.de
    Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
    Peter V. Gehler, Sebastian Nowozin
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