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        <title>Learning Tier-based Strictly 2-Local Languages</title>
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    <abstract>The Tier-based Strictly 2-Local (TSL2) languages are a class of formal languages which have been shown to model long-distance phonotactic generalizations in natural language (Heinz et al., 2011). This paper introduces the Tier-based Strictly 2-Local Inference Algorithm (2TSLIA), the first nonenumerative learner for the TSL2 languages. We prove the 2TSLIA is guaranteed to converge in polynomial time on a data sample whose size is bounded by a constant.</abstract>
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    <identifier type="doi">10.1162/tacl_a_00085</identifier>
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%0 Journal Article
%T Learning Tier-based Strictly 2-Local Languages
%A Jardine, Adam
%A Heinz, Jeffrey
%J Transactions of the Association for Computational Linguistics
%D 2016
%V 4
%I MIT Press
%C Cambridge, MA
%F jardine-heinz-2016-learning
%X The Tier-based Strictly 2-Local (TSL2) languages are a class of formal languages which have been shown to model long-distance phonotactic generalizations in natural language (Heinz et al., 2011). This paper introduces the Tier-based Strictly 2-Local Inference Algorithm (2TSLIA), the first nonenumerative learner for the TSL2 languages. We prove the 2TSLIA is guaranteed to converge in polynomial time on a data sample whose size is bounded by a constant.
%R 10.1162/tacl_a_00085
%U https://aclanthology.org/Q16-1007
%U https://doi.org/10.1162/tacl_a_00085
%P 87-98

Markdown (Informal)

[Learning Tier-based Strictly 2-Local Languages](https://aclanthology.org/Q16-1007) (Jardine & Heinz, TACL 2016)

• Learning Tier-based Strictly 2-Local Languages (Jardine & Heinz, TACL 2016)

ACL

• Adam Jardine and Jeffrey Heinz. 2016. Learning Tier-based Strictly 2-Local Languages. Transactions of the Association for Computational Linguistics, 4:87–98.