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|Title:||On conservative learning of recursively enumerable languages||Authors:||Gao, Z.
|Issue Date:||2013||Citation:||Gao, Z.,Jain, S.,Stephan, F. (2013). On conservative learning of recursively enumerable languages. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7921 LNCS : 181-190. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-39053-1_21||Abstract:||Conservative partial learning is a variant of partial learning whereby the learner, on a text for a target language L, outputs one index e with L = W e infinitely often and every further hypothesis d is output only finitely often and satisfies L ⊈ Wd. The present paper studies the learning strength of this notion, comparing it with other learnability criteria such as confident partial learning, explanatory learning, as well as behaviourally correct learning. It is further established that for classes comprising infinite sets, conservative partial learnability is in fact equivalent to explanatory learnability relative to the halting problem. © 2013 Springer-Verlag.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/113938||ISBN:||9783642390524||ISSN:||03029743||DOI:||10.1007/978-3-642-39053-1_21|
|Appears in Collections:||Staff Publications|
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