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Theoretical computer science / Electromagnetism / Topology / Connectivity / Applied mathematics / Electronics / Segmentation-based object categorization / Graphical models / Conditional random field / Machine learning


Max Margin AND/OR Graph Learning for Parsing the Human Body Long (Leo) Zhu Department of Statistics University of California, Los Angeles Yuanhao Chen
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Document Date: 2008-04-06 20:05:24


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City

New York / /

Company

Springer-Verlag New York Inc. / Cambridge University Press / Microsoft / /

Country

United States / /

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Facility

Statistics University of California / Los Angeles Yuanhao Chen University of Science / Computer Science University of California / /

IndustryTerm

model search using segmentation / least energy / inference algorithm / low energy / inner product / optimization algorithm / compositional algorithm / hybrid search / tractable learning algorithm / set algorithm / markov networks / computing / search space / energy terms / energy / /

Organization

Cambridge University / University of Science and Technology of China / Zhu Department / Statistics University / National Science Foundation / Department of Statistics / University of California / Los Angeles / /

Person

Max Margin / C. Rother / V / Max Margin Structure Learning / Alan Yuille / /

Position

model for parsing human body / MP / /

ProvinceOrState

New York / /

PublishedMedium

Journal of Machine Learning Research / /

Technology

working set algorithm / training algorithm / inference algorithm / Technology of China yhchen4@ustc.edu lzhu@stat.ucla.edu Yifei Lu Shanghai Jiao Tong University Chenxi Lin Microsoft Research Asia klux@sjtu.edu.cn chenxil@microsoft.com / machine learning / computationally tractable learning algorithm / compositional algorithm / optimization algorithm / /

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