Learning Maximal Margin Markov Networks via Tractable Convex Optimization
Показано, что обучение марковской сети общего вида может быть представлено в виде задачи выпуклой оптимизации. Основная идея метода заключается в использовании LP-релаксации (max,+)-задачи непосредственно при формулировании задачи обучения. It is shown that the learning of a general Markov network c...
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| Published in: | Управляющие системы и машины |
|---|---|
| Date: | 2011 |
| Main Authors: | Franc, V., Laskov, P. |
| Format: | Article |
| Language: | English |
| Published: |
Міжнародний науково-навчальний центр інформаційних технологій і систем НАН та МОН України
2011
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| Subjects: | |
| Online Access: | https://nasplib.isofts.kiev.ua/handle/123456789/82921 |
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| Journal Title: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Cite this: | Learning Maximal Margin Markov Networks via Tractable Convex Optimization / V. Franc, P. Laskov // Управляющие системы и машины. — 2011. — № 2. — С. 25-34. — Бібліогр.: 17 назв. — англ. |
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