Communications of the ACM
Some subclasses of context-free languages in NC1
Information Processing Letters
Crytographic limitations on learning Boolean formulae and finite automata
STOC '89 Proceedings of the twenty-first annual ACM symposium on Theory of computing
Learning simple deterministic languages
COLT '89 Proceedings of the second annual workshop on Computational learning theory
Learning context-free grammars from structural data in polynomial time
Theoretical Computer Science
The minimum consistent DFA problem cannot be approximated within any polynomial
Journal of the ACM (JACM)
Characteristic Sets for Polynomial Grammatical Inference
Machine Learning
Recent advances of grammatical inference
Theoretical Computer Science - Special issue on algorithmic learning theory
Context-free languages and pushdown automata
Handbook of formal languages, vol. 1
Learning DFA from Simple Examples
Machine Learning
On the Relationship between Models for Learning in Helpful Environments
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
GA-based Learning of Context-Free Grammars using Tabular Representations
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
A Hierarchy of Language Families Learnable by Regular Language Learners
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Inductive Inference, DFAs, and Computational Complexity
AII '89 Proceedings of the International Workshop on Analogical and Inductive Inference
On the Complexities of Linear LL(1) and LR(1) Grammars
FCT '93 Proceedings of the 9th International Symposium on Fundamentals of Computation Theory
A Characterization of Even Linear Languages and its Application to the Learning Problem
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
On Sufficient Conditions to Identify in the Limit Classes of Grammars from Polynomial Time and Data
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
LARS: A learning algorithm for rewriting systems
Machine Learning
A Polynomial Algorithm for the Inference of Context Free Languages
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Learning Context-Sensitive Languages from Linear Structural Information
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Polynomial Time Probabilistic Learning of a Subclass of Linear Languages with Queries
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
A bibliographical study of grammatical inference
Pattern Recognition
Using Contextual Representations to Efficiently Learn Context-Free Languages
The Journal of Machine Learning Research
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Streaming algorithms for language recognition problems
Theoretical Computer Science
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Linearity and determinism seem to be two essential conditions for polynomial language learning to be possible. We compare several definitions of deterministic linear grammars, and for a reasonable definition prove the existence of a canonical normal form. This enables us to obtain positive learning results in case of polynomial learning from a given set of both positive and negative examples. The resulting class is the largest one for which this type of results has been obtained so far.