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
Author
Mančev, DejanMentor
Todorović, BranimirCommittee members
Ćirić, Miroslav
Stanimirović, Predrag

Stanković, Miomir
Stoimenov, Leonid

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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.