Inference of Finite-State Transducers by Using Regular Grammars and Morphisms -- Computational Complexity of Problems on Probabilistic Grammars and Transducers -- Efficient Ambiguity Detection in C-NFA -- Learning Regular Languages Using Non Deterministic Finite Automata -- Smoothing Probabilistic Automata: An Error-Correcting Approach -- Inferring Subclasses of Contextual Languages -- Permutations and Control Sets for Learning Non-regular Language Families -- On the Complexity of Consistent Identification of Some Classes of Structure Languages -- Computation of Substring Probabilities in Stochastic Grammars -- A Comparative Study of Two Algorithms for Automata Identification -- The Induction of Temporal Grammatical Rules from Multivariate Time Series -- Identification in the Limit with Probability One of Stochastic Deterministic Finite Automata -- Iterated Transductions and Efficient Learning from Positive Data: A Unifying View -- An Inverse Limit of Context-Free Grammars – A New Approach to Identifiability in the Limit -- Synthesizing Context Free Grammars from Sample Strings Based on Inductive CYK Algorithm -- Combination of Estimation Algorithms and Grammatical Inference Techniques to Learn Stochastic Context-Free Grammars -- On the Relationship between Models for Learning in Helpful Environments -- Probabilistic k-Testable Tree Languages -- Learning Context-Free Grammars from Partially Structured Examples -- Identification of Tree Translation Rules from Examples -- Counting Extensional Differences in BC-Learning -- Constructive Learning of Context-Free Languages with a Subpansive Tree -- A Polynomial Time Learning Algorithm of Simple Deterministic Languages via Membership Queries and a Representative Sample -- Improve the Learning of Subsequential Transducers by Using Alignments andDictionaries.

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