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Categorical data / Probabilistic latent semantic analysis / Statistical natural language processing / Discriminative model / Support vector machine / Expectation–maximization algorithm / Kullback–Leibler divergence / Kernel / Pattern recognition / Statistics / Machine learning / Statistical classification


Proceedings of 2010 IEEE 17th International Conference on Image Processing September 26-29, 2010, Hong Kong COMBINING FREE ENERGY SCORE SPACES WITH INFORMATION THEORETIC KERNELS: APPLICATION TO SCENE CLASSIFICATION
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Document Date: 2012-06-26 09:41:00

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City

Kyoto / Kerkyra / Lisboa / Graz / Verona / San Diego / Newport / IEEE CVPR / Genova / /

Company

Cambridge University Press / Semigroup / /

Country

Japan / Jordan / Austria / Italy / Portugal / Greece / /

Currency

USD / /

Facility

University of Verona / /

IndustryTerm

experimental protocol / recent and top performing tools / variational free energy / free energy / energy score space / free energy score function / free energy score function defined / free energy score space / free-energy terms / off-theshelf tool / free energy score space embedding / learning algorithm / learning algorithms / energy / /

NaturalFeature

Newport Beach / /

Organization

Cambridge University / University of Verona / Instituto Superior T´ecnico / European Union / Instituto de Sistemas / /

Person

Corel Fei / L. Fei Fei / Fei Fei / T. Minka / M. Bicego / V / Tq / U. Castellani / V / /

Position

so-called Fisher / following feature extractor / feature extractor / model for that θ / adequate generative model for this problem / C. Bishop / /

ProgrammingLanguage

T / /

ProvinceOrState

New York / /

Technology

SVM learning algorithm / Image Processing / above mentioned EM-type algorithm / same experimental protocol / /

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