| 000 | 05104nam a22005775i 4500 | ||
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| 001 | 978-3-642-15488-1 | ||
| 003 | DE-He213 | ||
| 005 | 20140220084546.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 100909s2010 gw | s |||| 0|eng d | ||
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_a9783642154881 _9978-3-642-15488-1 |
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| 024 | 7 |
_a10.1007/978-3-642-15488-1 _2doi |
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| 050 | 4 | _aQ334-342 | |
| 050 | 4 | _aTJ210.2-211.495 | |
| 072 | 7 |
_aUYQ _2bicssc |
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| 072 | 7 |
_aCOM004000 _2bisacsh |
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| 082 | 0 | 4 |
_a006.3 _223 |
| 100 | 1 |
_aSempere, José M. _eeditor. |
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| 245 | 1 | 0 |
_aGrammatical Inference: Theoretical Results and Applications _h[electronic resource] : _b10th International Colloquium, ICGI 2010, Valencia, Spain, September 13-16, 2010. Proceedings / _cedited by José M. Sempere, Pedro García. |
| 264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010. |
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| 300 |
_aXI, 317p. 47 illus. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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_aLecture Notes in Computer Science, _x0302-9743 ; _v6339 |
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| 505 | 0 | _aInvited Talks -- Grammatical Inference and Games: Extended Abstract -- Molecules, Languages and Automata -- Regular Papers -- Inferring Regular Trace Languages from Positive and Negative Samples -- Distributional Learning of Some Context-Free Languages with a Minimally Adequate Teacher -- Learning Context Free Grammars with the Syntactic Concept Lattice -- Learning Automata Teams -- Exact DFA Identification Using SAT Solvers -- Learning Deterministic Finite Automata from Interleaved Strings -- Learning Regular Expressions from Representative Examples and Membership Queries -- Splitting of Learnable Classes -- PAC-Learning Unambiguous k,l-NTS??? Languages -- Bounding the Maximal Parsing Performance of Non-Terminally Separated Grammars -- CGE: A Sequential Learning Algorithm for Mealy Automata -- Using Grammar Induction to Model Adaptive Behavior of Networks of Collaborative Agents -- Transducer Inference by Assembling Specific Languages -- Sequences Classification by Least General Generalisations -- A Likelihood-Ratio Test for Identifying Probabilistic Deterministic Real-Time Automata from Positive Data -- A Local Search Algorithm for Grammatical Inference -- Polynomial-Time Identification of Multiple Context-Free Languages from Positive Data and Membership Queries -- Grammatical Inference as Class Discrimination -- Short Papers -- MDL in the Limit -- Grammatical Inference Algorithms in MATLAB -- A Non-deterministic Grammar Inference Algorithm Applied to the Cleavage Site Prediction Problem in Bioinformatics -- Learning PDFA with Asynchronous Transitions -- Grammar Inference Technology Applications in Software Engineering -- Hölder Norms and a Hierarchy Theorem for Parameterized Classes of CCG -- Learning of Church-Rosser Tree Rewriting Systems -- Generalizing over Several Learning Settings -- Rademacher Complexity and Grammar Induction Algorithms: What It May (Not) Tell Us -- Extracting Shallow Paraphrasing Schemata from Modern Greek Text Using Statistical Significance Testing and Supervised Learning -- Learning Subclasses of Parallel Communicating Grammar Systems -- Enhanced Suffix Arrays as Language Models: Virtual k-Testable Languages -- Learning Fuzzy Context-Free Grammar—A Preliminary Report -- Polynomial Time Identification of Strict Prefix Deterministic Finite State Transducers. | |
| 520 | _aThis book constitutes the refereed proceedings of the 10th International Colloquium on Grammatical Inference, ICGI 2010, held in Valencia, Spain, in September 2010. The 18 revised full papers and 14 revised short papers presented were carefully reviewed and selected from numerous submissions. The topics of the papers presented vary from theoretical results about the learning of different formal language classes (regular, context-free, context-sensitive, etc.) to application papers on bioinformatics, language modelling or software engineering. Furthermore there are two invited papers on the topics grammatical inference and games and molecules, languages, and automata. | ||
| 650 | 0 | _aComputer science. | |
| 650 | 0 | _aComputer software. | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aComputer vision. | |
| 650 | 0 | _aOptical pattern recognition. | |
| 650 | 1 | 4 | _aComputer Science. |
| 650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
| 650 | 2 | 4 | _aComputation by Abstract Devices. |
| 650 | 2 | 4 | _aPattern Recognition. |
| 650 | 2 | 4 | _aAlgorithm Analysis and Problem Complexity. |
| 650 | 2 | 4 | _aImage Processing and Computer Vision. |
| 650 | 2 | 4 | _aMathematical Logic and Formal Languages. |
| 700 | 1 |
_aGarcía, Pedro. _eeditor. |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783642154874 |
| 830 | 0 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v6339 |
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| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-15488-1 |
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| 912 | _aZDB-2-LNC | ||
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