Grammatical Inference: Algorithms and Applications
Springer Berlin (Verlag)
978-3-540-88008-0 (ISBN)
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Regular Papers.- Learning Meaning Before Syntax.- Schema-Guided Induction of Monadic Queries.- A Polynomial Algorithm for the Inference of Context Free Languages.- Learning Languages from Bounded Resources: The Case of the DFA and the Balls of Strings.- Relevant Representations for the Inference of Rational Stochastic Tree Languages.- Learning Commutative Regular Languages.- Learning Left-to-Right and Right-to-Left Iterative Languages.- Learning Bounded Unions of Noetherian Closed Set Systems Via Characteristic Sets.- A Learning Algorithm for Multi-dimensional Trees, or: Learning Beyond Context-Freeness.- On Learning Regular Expressions and Patterns Via Membership and Correction Queries.- State-Merging DFA Induction Algorithms with Mandatory Merge Constraints.- Using Multiplicity Automata to Identify Transducer Relations from Membership and Equivalence Queries.- Towards Feasible PAC-Learning of Probabilistic Deterministic Finite Automata.- Learning Context-Sensitive Languages from Linear Structural Information.- Polynomial Time Probabilistic Learning of a Subclass of Linear Languages with Queries.- How to Split Recursive Automata.- A Note on the Relationship between Different Types of Correction Queries.- Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering.- Polynomial Distinguishability of Timed Automata.- Evaluation and Comparison of Inferred Regular Grammars.- Identification in the Limit of k,l-Substitutable Context-Free Languages.- Poster Papers.- Learning Subclasses of Pure Pattern Languages.- Which Came First, the Grammar or the Lexicon?.- Learning Node Label Controlled Graph Grammars (Extended Abstract).- Inference of Uniquely Terminating EML.- Estimating Graph Parameters Using Graph Grammars.- Learning of Regular ?-TreeLanguages.- Inducing Regular Languages Using Grammar-Based Classifier System.- Problems with Evaluation of Unsupervised Empirical Grammatical Inference Systems.
| Erscheint lt. Verlag | 11.9.2008 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | XI, 305 p. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Algorithmic Learning • algorithms • applications of grammars • Biclustering • Computational Linguistics • context-free grammars • context-free languages • deterministic finite automata • Evaluation • finite-state transducers • grammar learning • Grammatical Inference • Hardcover, Softcover / Informatik, EDV/Informatik • HC/Informatik, EDV/Informatik • learning • Learning Algorithms • Learning classifier systems • lexical learning • linear languages • machine learning • Model-Based Testing • multi-dimensional trees • NATURAL • natural language learning • Neural networks • pattern recognition • polynomial learnability • probabilistic grammars • query learning • Regular Expressions • representative sample • Semantics • Statistical Learning • Unsupervised Learning |
| ISBN-10 | 3-540-88008-9 / 3540880089 |
| ISBN-13 | 978-3-540-88008-0 / 9783540880080 |
| Zustand | Neuware |
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