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Communication Dans Un Congrès Année : 2009

Maximum Margin Training of Gaussian HMMs for Handwriting Recognition

Résumé

Recent works for learning hidden Markov models in a discriminant way have focused on maximum margin training, which remains an open problem due to the lack of efficient optimization algorithms. We developed a new algorithm that is based on non convex optimization ideas and that may solve maximum margin learning of GHMMs within the standard setting of partially labeled training sets. We provide experimental results on both on-line handwriting and off-line handwriting recognition.
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Dates et versions

hal-01297957 , version 1 (05-04-2016)

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Trinh Minh Tri Do, Thierry Artières. Maximum Margin Training of Gaussian HMMs for Handwriting Recognition. International Conference on Document Analysis and Recognition (ICDAR), Jul 2009, Barcelona, Spain. pp.976-980, ⟨10.1109/ICDAR.2009.221⟩. ⟨hal-01297957⟩
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