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Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-16108-7_27
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dc.titleInductive inference of languages from samplings
dc.contributor.authorJain, S.
dc.contributor.authorKinber, E.
dc.date.accessioned2013-07-04T08:20:05Z
dc.date.available2013-07-04T08:20:05Z
dc.date.issued2010
dc.identifier.citationJain, S.,Kinber, E. (2010). Inductive inference of languages from samplings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6331 LNAI : 330-344. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-16108-7_27" target="_blank">https://doi.org/10.1007/978-3-642-16108-7_27</a>
dc.identifier.isbn3642161073
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41120
dc.description.abstractWe introduce, discuss, and study a model for inductive inference from samplings, formalizing an idea of learning different "projections" of languages. One set of our results addresses the problem of finding a uniform learner for all samplings of a language from a certain set when learners for particular samplings are available. Another set of results deals with extending learnability from a large natural set of samplings to larger sets. A number of open problems is formulated. © 2010 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-16108-7_27
dc.sourceScopus
dc.subjectInductive inference
dc.subjectsamplings
dc.subjectsublanguages
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/978-3-642-16108-7_27
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume6331 LNAI
dc.description.page330-344
dc.identifier.isiutNOT_IN_WOS
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