NTS languages are deterministic and congruential
Journal of Computer and System Sciences
Learning regular sets from queries and counterexamples
Information and Computation
Characteristic Sets for Polynomial Grammatical Inference
Machine Learning
Handbook of formal languages, vol. 3
Journal of Automata, Languages and Combinatorics - Special issue: selected papers of the second internaional workshop on Descriptional Complexity of Automata, Grammars and Related Structures (London, Ontario, Canada, July 27-29, 2000)
Machine Learning
Machine Learning
Counting with range concatenation grammars
Theoretical Computer Science - Algebraic methods in language processing
Learning Context-Free Grammars with a Simplicity Bias
ECML '00 Proceedings of the 11th European Conference on Machine Learning
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
Learning Stochastic Regular Grammars by Means of a State Merging Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
An incremental interactive algorithm for grammar inference
ICG! '96 Proceedings of the 3rd International Colloquium on Grammatical Inference: Learning Syntax from Sentences
Inductive Inference, DFAs, and Computational Complexity
AII '89 Proceedings of the International Workshop on Analogical and Inductive Inference
Inferring Deterministic Linear Languages
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Polynomial-time identification of very simple grammars from positive data
Theoretical Computer Science - Selected papers in honour of Setsuo Arikawa
A study of grammatical inference
A study of grammatical inference
Learning regular languages using RFSAs
Theoretical Computer Science - Special issue: Algorithmic learning theory
Generating all permutations by context-free grammars in Chomsky normal form
Theoretical Computer Science - Algebraic methods in language processing
LARS: A learning algorithm for rewriting systems
Machine Learning
Corpus-based induction of syntactic structure: models of dependency and constituency
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Marcus External Contextual Grammars: From One to Many Dimensions
Fundamenta Informaticae - Contagious Creativity - In Honor of the 80th Birthday of Professor Solomon Marcus
Polynomial Identification in the Limit of Substitutable Context-free Languages
The Journal of Machine Learning Research
Identification in the Limit of k,l-Substitutable Context-Free Languages
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Distributional learning of some context-free languages with a minimally adequate teacher
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
A learnable representation for syntax using residuated lattices
FG'09 Proceedings of the 14th international conference on Formal grammar
PAC-learning unambiguous NTS languages
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Inferring grammars for mildly context sensitive languages in polynomial-time
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
The tenjinno machine translation competition
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Distributional learning of abstract categorial grammars
LACL'11 Proceedings of the 6th international conference on Logical aspects of computational linguistics
Towards dual approaches for learning context-free grammars based on syntactic concept lattices
DLT'11 Proceedings of the 15th international conference on Developments in language theory
A language theoretic approach to syntactic structure
MOL'11 Proceedings of the 12th biennial conference on The mathematics of language
Distributional learning of simple context-free tree grammars
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
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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.