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Artificial intelligence / Support vector machine / Supervised learning / Margin classifier / Binary classification / Active learning / Boosting methods for object categorization / Linear classifier / Statistics / Machine learning / Statistical classification


¨ t Augsburg Universita Towards Learning with Objects in a Hierarchical Representation Nicolas Cebron
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Document Date: 2011-06-17 18:04:39

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City

Melville / Washington / DC / San Francisco / Newman / Cambridge / Asuncion / A. / Augsburg / /

Company

MIT Press / Morgan Kaufmann Publishers Inc. / /

Country

United States / /

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Facility

International Computer Science Institute / University of Augsburg / /

IndustryTerm

classification algorithm / graph mining / structure mining / /

Organization

HIERARCHICAL REPRESENTATION Nicolas Cebron Multimedia Computing Lab / German Academic Exchange Service / International Computer Science Institute / IEEE Computer Society / Informatik Institut / MIT / Nicolas Cebron Institut f¨ / University of Augsburg / /

Person

Nicolas Cebron / /

Position

editor / /

ProgrammingLanguage

DC / /

PublishedMedium

Journal of Machine Learning Research / Machine Learning / /

Technology

Data Mining / machine learning / classification algorithm / proposed algorithm / /

URL

http /

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