| Document Date: 2005-09-27 11:30:43
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City Park / Independence Way Princeton / Princeton / / Company NEC / FR NEC Laboratories America / ORG NEC Laboratories America / / Country United States / / Facility EDU The Pennsylvania State University University / / IndustryTerm τ-approximate solution / dot products / online setup / Online LASVM After / online process / Online and Active Learning Antoine Bordes ANTOINE / dot product / online iteration / Online Learning Algorithms / Online Iterations / above algorithm / online kernel classifier / online setting / search direction / online kernel methods / Online LASVM algorithm / direction search / online kernel classifiers / Online Iterations Let / Online SVM / direction search computations / 2τ-approximate solution / Online SVM algorithm / stochastic optimization algorithm / Φ-machine learning algorithms / online algorithm / stochastic algorithm / Online algorithms / numerical algorithms / Online LASVM / approximate solutions / dimensional learning systems / learning algorithm / Online LASVM This section / / Organization Ecole Sup´erieure de Physique / SVM QP / The Pennsylvania State University University / / Person Jason Weston / Ai / Antoine Bordes / / Position Editor / Singer / / ProvinceOrState New Jersey / Pennsylvania / / PublishedMedium Journal of Machine Learning Research / / Technology online algorithm / online SVM algorithm / stochastic algorithm / Blocks The LASVM algorithm / Φ-machine learning algorithms / LASVM algorithm / Machine Learning / stochastic optimization algorithm / learning algorithm / EARNING SMO Algorithm / Online LASVM algorithm / Perceptron algorithm / online learning algorithms / Kernel Perceptron algorithm / SMO algorithm / / URL http /
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Journal of Machine Learning Research–1619 Submitted 3/05; Published 9/05 Fast Kernel Classifiers with Online and Active Learning