Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10994-011-5238-7
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dc.titleIterative learning from texts and counterexamples using additional information
dc.contributor.authorJain, S.
dc.contributor.authorKinber, E.
dc.date.accessioned2013-07-04T07:33:48Z
dc.date.available2013-07-04T07:33:48Z
dc.date.issued2011
dc.identifier.citationJain, S., Kinber, E. (2011). Iterative learning from texts and counterexamples using additional information. Machine Learning 84 (3) : 291-333. ScholarBank@NUS Repository. https://doi.org/10.1007/s10994-011-5238-7
dc.identifier.issn08856125
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39093
dc.description.abstractA variant of iterative learning in the limit (cf. Lange and Zeugmann 1996) is studied when a learner gets negative examples refuting conjectures containing data in excess of the target language and uses additional information of the following four types: (a) memorizing up to n input elements seen so far; (b) up to n feedback memberships queries (testing if an item is a member of the input seen so far); (c) the number of input elements seen so far; (d) the maximal element of the input seen so far. We explore how additional information available to such learners (defined and studied in Jain and Kinber 2007) may help. In particular, we show that adding the maximal element or the number of elements seen so far helps such learners to infer any indexed class of languages class-preservingly (using a descriptive numbering defining the class)-as it is proved in Jain and Kinber (2007), this is not possible without using additional information. We also study how, in the given context, different types of additional information fare against each other, and establish hierarchies of learners memorizing n+1 versus n input elements seen and n+1 versus n feedback membership queries. © 2011 The Author(s).
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s10994-011-5238-7
dc.sourceScopus
dc.subjectFeedback
dc.subjectInductive inference
dc.subjectIterative learning
dc.subjectMemory limitation
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/s10994-011-5238-7
dc.description.sourcetitleMachine Learning
dc.description.volume84
dc.description.issue3
dc.description.page291-333
dc.description.codenMALEE
dc.identifier.isiut000293297200002
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