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1
Strong Learning of Probabilistic Tree Adjoining Grammars
In: Proceedings of the Society for Computation in Linguistics (2021)
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2
Consistent unsupervised estimators for anchored PCFGs
In: Proceedings of the Society for Computation in Linguistics (2021)
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3
Consistent Unsupervised Estimators for Anchored PCFGs
In: Transactions of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03410673 ; Transactions of the Association for Computational Linguistics, 2020, 8, ⟨10.1162/tacl_a_00323⟩ (2020)
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4
Consistent Unsupervised Estimators for Anchored PCFGs
In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 409-422 (2020) (2020)
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5
Empiricism and language learnability
Chater, Nick; Clark, Alexander; Goldsmith, John. - Oxford : Oxford University Press, 2015
MPI für Psycholinguistik
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6
Learnability
In: The handbook of language emergence (New York, 2015), p. 379-395
MPI für Psycholinguistik
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7
The Handbook of Computational Linguistics and Natural Language Processing
Clark, Alexander Herausgeber]. - New York, NY : John Wiley & Sons, 2013
DNB Subject Category Language
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8
Complexity in Language Acquisition
In: Topics in cognitive science. - Hoboken, NJ [u.a.] : Wiley 5 (2013) 1, 89-110
OLC Linguistik
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9
The Handbook of Computational Linguistics and Natural Language Processing
Clark, Alexander [Herausgeber]; Fox, Chris [Herausgeber]; Lappin, Shalom [Herausgeber]. - New York, NY : Wiley, J, 2012
DNB Subject Category Language
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10
Changing the lexicon of ‘Cardiac Rehabilitation’: a progressive step
Briffa, Tom G; Neubeck, Lis; Clark, Alexander M. - : SAGE Publications, 2012
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11
Linguistic nativism and the poverty of the stimulus
Lappin, Shalom; Clark, Alexander. - Malden, Mass. [u.a.] : Wiley-Blackwell, 2011
BLLDB
UB Frankfurt Linguistik
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12
Computational models of first language acquisition special issue of research on language and computation
In: Research on language and computation. - London : King's College 8 (2011) 2-3, 101-106
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OLC Linguistik
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13
Introduction to the special topic on grammar induction, representation of language and language learning
Glowacka, Dorota; Shawe-Taylor, John; Clark, Alexander. - : Microtome Publishing, 2011
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14
The Handbook of Computational Linguistics and Natural Language Processing
Clark, Alexander Herausgeber]. - New York, NY : John Wiley & Sons, 2010
DNB Subject Category Language
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15
The handbook of computational linguistics and natural language processing
Clark, Alexander. - Oxford; Cambridge, Mass. : Blackwell Publ., 2010
Leibniz-Zentrum Allgemeine Sprachwissenschaft
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16
The handbook of computational linguistics and natural language processing
Clark, Alexander (Hrsg.). - Chichester [u.a.] : Wiley-Blackwell, 2010
UB Frankfurt Linguistik
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17
The handbook of computational linguistics and natural language processing
Fox, Chris (Hrsg.); Lappin, Shalom (Hrsg.); Clark, Alexander (Hrsg.). - Chichester [u.a.] : Wiley-Blackwell, 2010
BLLDB
UB Frankfurt Linguistik
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18
Using Contextual Representations to Efficiently Learn Context-Free Languages
In: ISSN: 1532-4435 ; EISSN: 1533-7928 ; Journal of Machine Learning Research ; https://hal.archives-ouvertes.fr/hal-00607098 ; Journal of Machine Learning Research, Microtome Publishing, 2010, 11, pp.2707-2744 (2010)
Abstract: International audience ; We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. We achieve this result by moving to a novel representation, called Contextual Binary Feature Grammars (CBFGs), which are capable of representing richly structured context-free languages as well as some context sensitive languages. These representations explicitly model the lattice structure of the distribution of a set of substrings and can be inferred using a generalisation of distributional learning. This formalism is an attempt to bridge the gap between simple learnable classes and the sorts of highly expressive representations necessary for linguistic representation: it allows the learnability of a large class of context-free languages, that includes all regular languages and those context-free languages that satisfy two simple constraints. The formalism and the algorithm seem well suited to natural language and in particular to the modeling of first language acquisition. Preliminary experimental results confirm the effectiveness of this approach.
Keyword: [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; context-free language; grammatical inference; membership queries; positive data only
URL: https://hal.archives-ouvertes.fr/hal-00607098/document
https://hal.archives-ouvertes.fr/hal-00607098
https://hal.archives-ouvertes.fr/hal-00607098/file/Learning_CBFG.pdf
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19
Patients' experiences of disruptions associated with post-stroke dysarthria
In: International journal of language & communication disorders. - Oxford : Wiley-Blackwell 43 (2008) 2, 135-153
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OLC Linguistik
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20
Grammatical Inference: Algorithms and Applications : 9th International Colloquium, ICGI 2008 Saint-Malo, France, September 22-24, 2008 Proceedings
Clark, Alexander (Herausgeber); Miclet, Laurent (Herausgeber); Coste, François (Herausgeber). - Berlin, Heidelberg : Springer Berlin Heidelberg, 2008
BLLDB
UB Frankfurt Linguistik
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