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Algorithmic Learning Theory: 4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993. Proceedings Klaus P. Jantke Editor
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This volume contains all the papers that were presented at the Fourth Workshop on Algorithmic Learning Theory, held in Tokyo in November 1993. In addition to 3 invited papers, 29 papers w… Altro …

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This volume contains all the papers that were presented at the Fourth Workshop on Algorithmic Learning Theory, held in Tokyo in November 1993. In addition to 3 invited papers, 29 papers w… Altro …

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Algorithmic Learning Theory: 4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993. Proceedings (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence) - Kobayashi, Shigenobu, Etsuji Tomita and Takashi Yokomori
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Algorithmic Learning Theory: 4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993. Proceedings (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence) - edizione con copertina flessibile

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Algorithmic Learning Theory - Klaus P. Jantke; Shigenobu Kobayashi; Etsuji Tomita; Takashi Yokomori
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Klaus P. Jantke; Shigenobu Kobayashi; Etsuji Tomita; Takashi Yokomori:
Algorithmic Learning Theory - edizione con copertina flessibile

1993, ISBN: 9783540573708

4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993. Proceedings, Buch, Softcover, [PU: Springer Berlin], Springer Berlin, 1993

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Algorithmic Learning Theory: 4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993. Proceedings Klaus P. Jantke Editor

This volume contains all the papers that were presented atthe Fourth Workshop on Algorithmic Learning Theory, held inTokyo in November 1993. In addition to 3 invited papers, 29papers were selected from 47 submitted extended abstracts.The workshop was the fourth in a series of ALT workshops,whose focus is on theories of machine learning and theapplication of such theories to real-world learningproblems. The ALT workshops have been held annually since1990, sponsored by the Japanese Society for ArtificialIntelligence. The volume is organized into parts oninductive logic and inference, inductive inference,approximate learning, query learning, explanation-basedlearning, and new learning paradigms.

Informazioni dettagliate del libro - Algorithmic Learning Theory: 4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993. Proceedings Klaus P. Jantke Editor


EAN (ISBN-13): 9783540573708
ISBN (ISBN-10): 3540573704
Copertina rigida
Copertina flessibile
Anno di pubblicazione: 1993
Editore: Springer Berlin Heidelberg Core >1 >T
444 Pagine
Peso: 0,666 kg
Lingua: eng/Englisch

Libro nella banca dati dal 2007-10-27T23:31:43+02:00 (Zurich)
Pagina di dettaglio ultima modifica in 2023-12-24T06:07:37+01:00 (Zurich)
ISBN/EAN: 9783540573708

ISBN - Stili di scrittura alternativi:
3-540-57370-4, 978-3-540-57370-8
Stili di scrittura alternativi e concetti di ricerca simili:
Autore del libro : tomita, takashi, learning international, shigenobu kobayashi, shinohara, ets, tom, klaus held
Titolo del libro: workshop 1993, ing, algorithmic learning theory, alt japan, tokyo certain, lecture notes artificial intelligence, computer


Dati dell'editore

Autore: Klaus P. Jantke; Shigenobu Kobayashi; Etsuji Tomita; Takashi Yokomori
Titolo: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Algorithmic Learning Theory - 4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993. Proceedings
Editore: Springer; Springer Berlin
428 Pagine
Anno di pubblicazione: 1993-10-20
Berlin; Heidelberg; DE
Stampato / Fatto in
Peso: 1,380 kg
Lingua: Inglese
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
POD
XI, 428 p.

BC; Artificial Intelligence; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; algorithm; algorithmic learning theory; algorithms; artificial intelligence; intelligence; learning; learning theory; logic; machine learning; Mathematics, general; Theory of Computation; Computation by Abstract Devices; Artificial Intelligence; Mathematics; Theory of Computation; Mathematik; Theoretische Informatik; EA

Identifying and using patterns in sequential data.- Learning theory toward Genome Informatics.- Optimal layered learning: A PAC approach to incremental sampling.- Reformulation of explanation by linear logic toward logic for explanation.- Towards efficient inductive synthesis of expressions from input/output examples.- A typed ?-calculus for proving-by-example and bottom-up generalization procedure.- Case-based representation and learning of pattern languages.- Inductive resolution.- Generalized unification as background knowledge in learning logic programs.- Inductive inference machines that can refute hypothesis spaces.- On the duality between mechanistic learners and what it is they learn.- On aggregating teams of learning machines.- Learning with growing quality.- Use of reduction arguments in determining Popperian FIN-type learning capabilities.- Properties of language classes with finite elasticity.- Uniform characterizations of various kinds of language learning.- How to invent characterizable inference methods for regular languages.- Neural Discriminant Analysis.- A new algorithm for automatic configuration of Hidden Markov Models.- On the VC-dimension of depth four threshold circuits and the complexity of Boolean-valued functions.- On the sample complexity of consistent learning with one-sided error.- Complexity of computing Vapnik-Chervonenkis dimension.- ?-approximations of k-label spaces.- Exact learning of linear combinations of monotone terms from function value queries.- Thue systems and DNA — A learning algorithm for a subclass.- The VC-dimensions of finite automata with n states.- Unifying learning methods by colored digraphs.- A perceptual criterion for visually controlling learning.- Learning strategies using decision lists.- A decomposition based induction model for discovering concept clusters from databases.- Algebraic structure of some learning systems.- Induction of probabilistic rules based on rough set theory.

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