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Inference of reversible languages
 Journal of the ACM, JACM
, 1982
"... Abstract. A famdy of efficient algorithms for referring certain subclasses of the regular languages from fmtte posttwe samples is presented These subclasses are the kreversible languages, for k = 0, 1, 2,.... For each k there is an algorithm for finding the smallest kreversible language containing ..."
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Cited by 162 (5 self)
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Abstract. A famdy of efficient algorithms for referring certain subclasses of the regular languages from fmtte posttwe samples is presented These subclasses are the kreversible languages, for k = 0, 1, 2,.... For each k there is an algorithm for finding the smallest kreversible language containing any fimte posluve sample. It ts shown how to use this algorithm to do correct identification m the ILmlt of the kreversible languages from posmve data A reversible language is one that Is kreverstble for some k _ _ 0. An efficient algonthrn is presented for mfernng reversible languages from posmve and negative examples, and it is shown that it leads to correct identification m the hmlt of the class of reversible languages. Numerous examples are gtven to dlustrate the algorithms and their behawor
Learning of ContextFree Languages: A Survey of the Literature
 REP
, 1996
"... We survey methods for learning contextfree languages (CFL's) in the theoretical computer science literature. We first present some important negative results. Then, we consider five types of methods: those that take text as input, those that take structural information as input, those that rely on ..."
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Cited by 21 (0 self)
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We survey methods for learning contextfree languages (CFL's) in the theoretical computer science literature. We first present some important negative results. Then, we consider five types of methods: those that take text as input, those that take structural information as input, those that rely on CFL formalisms that are not based on contextfree grammars, those which learn subclasses of CFL's, and stochastic methods. A description of the subclasses of CFL's considered is provided, as is an extensive bibliography.
Algebraic properties of structured contextfree languages: old approaches and . . .
, 2009
"... ..."
Advances in Learning Formal Languages
"... Abstract—we present an overview in the advances related to the learning of formal languages i.e. development in the grammatical inference research. The problem of learning correct grammars for the unknown languages is known as grammatical inference. It is considered a main subject of inductive infer ..."
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Abstract—we present an overview in the advances related to the learning of formal languages i.e. development in the grammatical inference research. The problem of learning correct grammars for the unknown languages is known as grammatical inference. It is considered a main subject of inductive inference, and grammars are important representations to be investigated in machine learning from both theoretical and practical points of view. Application area of grammatical inference is increasing day by day, and it is still required to find a task where grammatical inference models have done much better than other machine learning or pattern recognition programs. However, it is known that making research in this area is a computationally hard problem. This paper mainly explores the area, its applications, various learning paradigms, the case of contextfree grammars, challenges, recent trends etc., and cites the important literature on these. Index Terms — machine learning, grammatical inference, learning model, formal language, contextfree grammars D I.