Polynomial Conditional Random Fields for signal processing

Trinh Minh Tri Do 1 Thierry Artières 1
1 MALIRE - Machine Learning and Information Retrieval
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : We describe Polynomial Conditional Random Fields for signal processing tasks. It is a hybrid model that combines the ability of Polynomial Hidden Markov models for modeling complex dynamic signals and the discriminant power of Conditional Random Fields. We detail the learning of these models and report experimental results on handwriting recognition.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01337124
Contributor : Lip6 Publications <>
Submitted on : Friday, June 24, 2016 - 3:11:27 PM
Last modification on : Thursday, September 19, 2019 - 2:20:04 PM

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  • HAL Id : hal-01337124, version 1

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Trinh Minh Tri Do, Thierry Artières. Polynomial Conditional Random Fields for signal processing. European Conference on Artificial Intelligence (ECAI'06), Aug 2006, Riva del Garda, Italy. pp.797-798. ⟨hal-01337124⟩

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