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Treniranje strukturnih klasifikatora za različite funkcije gubitaka sa primenom na probleme klasifikovanja sekvenci

Training Structured Classifiers for Different Loss Functions with the Application to Sequence Labeling Problems

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2015
Disertacija168.pdf (3.844Mb)
Mancev_Dejan.pdf (1.662Mb)
Author
Mančev, Dejan
Mentor
Todorović, Branimir
Committee members
Ćirić, Miroslav
Stanimirović, Predrag
Stanković, Miomir
Stoimenov, Leonid
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Abstract
This thesis presents algorithms for training structured classifiers over different loss functions. It introduces a new primal subgradient method for the optimization of average sum loss, several extensions of max-margin classifiers to the k-best case, a sequential dual method for the structured ramp loss optimization, It considers different decoding algorithms over semirings and presents an organization of a two-structured-model committee in order to improve the results. It includes theoretical analysis of introduced algorithms, as well as experimental results on sequence labelling problems in natural language processing.
Faculty:
University of Niš, Faculty of Science and Mathematics
Date:
06-07-2015
Keywords:
Računarske nauke / structured learning / strukturno učenje / klasifikacija sekvenci / sequence labeling
[ Google Scholar ]
URI
http://nardus.mpn.gov.rs/handle/123456789/4312
http://eteze.ni.ac.rs/application/showtheses?thesesId=2252
https://fedorani.ni.ac.rs/fedora/get/o:1009/bdef:Content/download
http://vbs.rs/scripts/cobiss?command=DISPLAY&base=70052&RID=1025057769

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