کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
534554 870265 2014 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Joint semi-supervised learning of Hidden Conditional Random Fields and Hidden Markov Models
ترجمه فارسی عنوان
یادگیری نیمه نظارت شده از زمینه های تصادفی مخفی و مدل های مخفی مارکوف
کلمات کلیدی
مدل مارکف مخفی، زمینه های تصادفی محرمانه مخفی، یادگیری نیمه نظارتی، همکاری آموزشی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• Hidden Markov Models and Hidden Conditional Random Fields.
• Semi-supervised learning for hidden state markovian models.
• Joint learning of a pair of discriminative-generative models.
• Financial chart pattern classification.
• Handwriting character recognition.

Although semi-supervised learning has generated great interest for designing classifiers on static patterns, there has been comparatively fewer works on semi-supervised learning for structured outputs and in particular for sequences. We investigate semi-supervised approaches for learning hidden state conditional random fields for sequence classification. We propose a new approach that iteratively learns a pair of discriminative-generative models, namely Hidden Markov Models (HMMs) and Hidden Conditional Random Fields (HCRFs). Our method builds on simple strategies for semi-supervised learning of HMMs and on strategies for initializing HCRFs from HMMs. We investigate the behavior of the method on artificial data and provide experimental results for two real problems, handwritten character recognition and financial chart pattern recognition. We compare our approach with state of the art semi-supervised methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 37, 1 February 2014, Pages 161–171
نویسندگان
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