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Partially distribution-free learning of regular languages from positive samples
2004
Proceedings of the 20th international conference on Computational Linguistics - COLING '04
unpublished
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We then present a simple learning algorithm for regular languages, and a self-contained proof that it learns according to this partially distribution free criterion. ...
Efficient algorithms that can reliably learn these languages, and which must in realistic applications only use positive samples, are necessary. ...
In a distribution-free setting this is not learnable from positive and negative samples, nor a fortiori from positive samples alone. ...
doi:10.3115/1220355.1220368
fatcat:3zyq54fb2vbjvbkpkohyrjp6zm
PAC Learning of Some Subclasses of Context-Free Grammars with Basic Distributional Properties from Positive Data
[chapter]
2013
Lecture Notes in Computer Science
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This paper shows that several subclasses of contextfree languages that are known to be exactly learnable with membership queries by distributional learning techniques are pac learnable from positive data ...
In recent years different interesting subclasses of cfls have been found to be learnable by techniques generically called distributional learning. ...
Clark [2] has shown that unambiguous nts languages are pac learnable from partially distribution-free positive data only based on distributional learning techniques. ...
doi:10.1007/978-3-642-40935-6_11
fatcat:fkr3eznpxvhttei6tl3h7pio5e
Grammatical Inference in Software Engineering: An Overview of the State of the Art
[chapter]
2013
Lecture Notes in Computer Science
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examining the sentences of an unknown language. ...
Software engineering can also benefit from grammatical inference. ...
It is a context-free grammar with positive samples only, and Gold proved learning a superfinite language in the limit from positive-only samples is impossible [24] . ...
doi:10.1007/978-3-642-36089-3_12
fatcat:3qp3xzhhqjgwdhguesrjnvotra
Ten Open Problems in Grammatical Inference
[chapter]
2006
Lecture Notes in Computer Science
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They cover the areas of polynomial learning models, learning from ordered alphabets, learning deterministic Pomdps, learning negotiation processes, learning from context-free background knowledge. ...
We propose 10 different open problems in the field of grammatical inference. In all cases, problems are theoretically oriented but correspond to practical questions. ...
Work with Henning Fernau on polynomial learning is where the ideas in section 3 come from. Philippe Jaillon gave me the initial ideas for the negotiation problem in section 9. Discussions with ...
doi:10.1007/11872436_4
fatcat:5snm4lpumbhw5e7ffh5vwxzhum
A survey of grammatical inference in software engineering
2014
Science of Computer Programming
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examining the sentences of an unknown language. ...
Software engineering can also benefit from grammatical inference. ...
It is a context-free grammar with positive samples only, and Gold proved learning a superfinite language in the limit from positive-only samples is impossible [34] . while limit > a do begin if a > max ...
doi:10.1016/j.scico.2014.05.008
fatcat:xwasotc745ekbhaoq2n43vrufm
A bibliographical study of grammatical inference
2005
Pattern Recognition
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The field of grammatical inference (also known as grammar induction) is transversal to a number of research areas including machine learning, formal language theory, syntactic and structural pattern recognition ...
The goal of this paper is to introduce a certain number of papers related with grammatical inference. ...
An unknown distribution over all possible examples exists, and examples are sampled under this distribution. Learning is done from this sample, and the result is tested under the same distribution. ...
doi:10.1016/j.patcog.2005.01.003
fatcat:62qwskiqcvddjobakbdshwebqq
1. Formal grammar and information theory: together again?
[chapter]
2002
Current issues in linguistic theory
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of language by counting occurrences of linguistic events in very large bodies of text and speech. ...
Zellig Harris had advocated a close alliance between grammatical and information-theoretic principles in the analysis of natural language, and early formal-language theory provided another strong link ...
Generalization While Harris discussed the functional role of distributional regularities in language, he proposed no speci c mechanisms by which language users could take advantage of those regularities ...
doi:10.1075/cilt.229.05per
fatcat:ac7rl72jzzf5fmdc6ax6zc5gb4
LANGUAGE LEARNING, POWER LAWS, AND SEXUAL SELECTION
2006
The Evolution of Language
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The corollary, however, is that rare unpredictable properties of language which do not follow from some regularity manifest during the learning period should be unstable and, therefore, rarely observed ...
mean that can be accurately estimated from a representative sample of the population. ...
doi:10.1142/9789812774262_0003
fatcat:chvm3nh4qbb3nf3aata2ligxwu
Language learning, power laws, and sexual selection
2007
Mind & Society
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The corollary, however, is that rare unpredictable properties of language which do not follow from some regularity manifest during the learning period should be unstable and, therefore, rarely observed ...
mean that can be accurately estimated from a representative sample of the population. ...
doi:10.1007/s11299-007-0040-8
fatcat:z2sp5utuavha3nmzaswdohowue
Editors' Introduction
[chapter]
2013
Lecture Notes in Computer Science
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He also studied the learnability of regular languages and context-free languages; a sample result, obtained in collaboration with Franck Thollard, is that the class of regular languages can be PAC-learned ...
In his invited talk Towards General Algorithms for Grammatical Inference, Alexander Clark deals with the learning of context-free languages and multiple context-free languages. ...
He also studied the learnability of regular languages and context-free languages; a sample result, obtained in collaboration with Franck Thollard, is that the class of regular languages can be PAC-learned ...
doi:10.1007/978-3-642-40935-6_1
fatcat:pchrsvhjezfbvh6dfplqhxhgcy
Learning deterministic regular expressions for the inference of schemas from XML data
2008
Proceeding of the 17th international conference on World Wide Web - WWW '08
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Unfortunately, there is no algorithm capable of learning the complete class of deterministic regular expressions from positive examples only, as we will show. ...
Inferring an appropriate DTD or XML Schema Definition (XSD) for a given collection of XML documents essentially reduces to learning deterministic regular expressions from sets of positive example words ...
Most of the learning of regular languages from positive examples in the computational learning community is directed towards inference of automata as opposed to inference of regular expressions [5, 43 ...
doi:10.1145/1367497.1367609
dblp:conf/www/BexGNV08
fatcat:bqs6npqyi5eaxlzv5n3ktgb6di
Learning Deterministic Regular Expressions for the Inference of Schemas from XML Data
2010
ACM Transactions on the Web
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Unfortunately, there is no algorithm capable of learning the complete class of deterministic regular expressions from positive examples only, as we will show. ...
Inferring an appropriate DTD or XML Schema Definition (XSD) for a given collection of XML documents essentially reduces to learning deterministic regular expressions from sets of positive example words ...
Most of the learning of regular languages from positive examples in the computational learning community is directed towards inference of automata as opposed to inference of regular expressions [5, 43 ...
doi:10.1145/1841909.1841911
fatcat:hre7agfyuzhudl3xwlaxxd4xg4
Formal grammar and information theory: together again?
2000
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
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of language by counting occurrences of linguistic events in very large bodies of text and speech. ...
Zellig Harris had advocated a close alliance between grammatical and information-theoretic principles in the analysis of natural language, and early formal-language theory provided another strong link ...
in the study of language that most of my work derives from. ...
doi:10.1098/rsta.2000.0583
fatcat:pfm2cu4eargphjxrdieln5auti
Neuro-Symbolic Program Synthesis
[article]
2016
arXiv
pre-print
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Given a set of input-output examples, these architectures are able to learn mappings that generalize to new test inputs. ...
We demonstrate the effectiveness of our approach by applying it to the rich and complex domain of regular expression based string transformations. ...
The semantics of position logic (r, k, Start) is to return the Start of k th match of r in v from the beginning (if k > 0) or from the end (if k < 0). ...
arXiv:1611.01855v1
fatcat:osn7netvtnehpcl7l4n2ryl6o4
Learning Languages with Help
[chapter]
2002
Lecture Notes in Computer Science
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We present in this paper the possibility of learning when presented with additional information such as the knowledge that the hidden language belongs to some known language, or that the strings are typed ...
Grammatical inference consists in learning formal grammars for unknown languages when given learning data. Classically this data is raw: strings that belong to the language or that do not. ...
In this setting the learner is asked to learn from a learning sample, i.e. a finite set of strings, each string labeled by '+' if the string is a positive instance of the language (an element of L), or ...
doi:10.1007/3-540-45790-9_13
fatcat:adbjrahojfejxieqmglom6vnay
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