Learning Pairwise Disjoint Simple Languages from Positive Examples

A classical problem in grammatical inference is to identify a deterministic finite automaton (DFA) from a set of positive and negative examples. In this paper, we address the related - yet seemingly novel - problem of identifying a set of DFAs from examples that belong to different unknown simple re...

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Bibliographic Details
Main Authors: Linard, Alexis, Smetsers, Rick, Vaandrager, Frits, Waqas, Umar, van Pinxten, Joost, Verwer, Sicco
Format: Report
Language:unknown
Published: arXiv 2017
Subjects:
Machine Learning cs.LG
Formal Languages and Automata Theory cs.FL
FOS Computer and information sciences
Iceland
Online Access:https://dx.doi.org/10.48550/arxiv.1706.01663
https://arxiv.org/abs/1706.01663
id ftdatacite:10.48550/arxiv.1706.01663
record_format openpolar
spelling ftdatacite:10.48550/arxiv.1706.01663 2023-05-15T16:48:26+02:00 Learning Pairwise Disjoint Simple Languages from Positive Examples Linard, Alexis Smetsers, Rick Vaandrager, Frits Waqas, Umar van Pinxten, Joost Verwer, Sicco 2017 https://dx.doi.org/10.48550/arxiv.1706.01663 https://arxiv.org/abs/1706.01663 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Machine Learning cs.LG Formal Languages and Automata Theory cs.FL FOS Computer and information sciences Preprint Article article CreativeWork 2017 ftdatacite https://doi.org/10.48550/arxiv.1706.01663 2022-04-01T10:20:29Z A classical problem in grammatical inference is to identify a deterministic finite automaton (DFA) from a set of positive and negative examples. In this paper, we address the related - yet seemingly novel - problem of identifying a set of DFAs from examples that belong to different unknown simple regular languages. We propose two methods based on compression for clustering the observed positive examples. We apply our methods to a set of print jobs submitted to large industrial printers. : This paper has been accepted at the Learning and Automata (LearnAut) Workshop, LICS 2017 (Reykjavik, Iceland) Report Iceland DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Machine Learning cs.LG
Formal Languages and Automata Theory cs.FL
FOS Computer and information sciences
spellingShingle Machine Learning cs.LG
Formal Languages and Automata Theory cs.FL
FOS Computer and information sciences
Linard, Alexis
Smetsers, Rick
Vaandrager, Frits
Waqas, Umar
van Pinxten, Joost
Verwer, Sicco
Learning Pairwise Disjoint Simple Languages from Positive Examples
topic_facet Machine Learning cs.LG
Formal Languages and Automata Theory cs.FL
FOS Computer and information sciences
description A classical problem in grammatical inference is to identify a deterministic finite automaton (DFA) from a set of positive and negative examples. In this paper, we address the related - yet seemingly novel - problem of identifying a set of DFAs from examples that belong to different unknown simple regular languages. We propose two methods based on compression for clustering the observed positive examples. We apply our methods to a set of print jobs submitted to large industrial printers. : This paper has been accepted at the Learning and Automata (LearnAut) Workshop, LICS 2017 (Reykjavik, Iceland)
format Report
author Linard, Alexis
Smetsers, Rick
Vaandrager, Frits
Waqas, Umar
van Pinxten, Joost
Verwer, Sicco
author_facet Linard, Alexis
Smetsers, Rick
Vaandrager, Frits
Waqas, Umar
van Pinxten, Joost
Verwer, Sicco
author_sort Linard, Alexis
title Learning Pairwise Disjoint Simple Languages from Positive Examples
title_short Learning Pairwise Disjoint Simple Languages from Positive Examples
title_full Learning Pairwise Disjoint Simple Languages from Positive Examples
title_fullStr Learning Pairwise Disjoint Simple Languages from Positive Examples
title_full_unstemmed Learning Pairwise Disjoint Simple Languages from Positive Examples
title_sort learning pairwise disjoint simple languages from positive examples
publisher arXiv
publishDate 2017
url https://dx.doi.org/10.48550/arxiv.1706.01663
https://arxiv.org/abs/1706.01663
genre Iceland
genre_facet Iceland
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.1706.01663
_version_ 1766038528928514048

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