Statistical Relational Learning With Unconventional String Models

Statistical Relational Learning With Unconventional String Models

This paper shows how methods from statistical relational learning can be used to address problems in grammatical inference using model-theoretic representations of strings. These model-theoretic representations are the basis of representing formal languages logically. Conventional representations in...

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Bibliographic Details
Main Authors: Mai H. Vu, Ashkan Zehfroosh, Kristina Strother-Garcia, Michael Sebok, Jeffrey Heinz, Herbert G. Tanner
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-07-01
Series:Frontiers in Robotics and AI
Subjects:
statistical relational learning
Markov logic networks
grammatical inference
formal language theory
model theory
phonology
Online Access:https://www.frontiersin.org/article/10.3389/frobt.2018.00076/full

Internet

https://www.frontiersin.org/article/10.3389/frobt.2018.00076/full

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