Algorithmic learning theory : 10th International Conference, ALT 99, Tokyo, Japan, December 6-8, 1999 : proceedings
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| Autor Corporativo: | |
| Outros autores: | |
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Series: | Lecture notes in computer science. Lecture notes in artificial intelligence
1720 |
| Sujets: | |
| Acceso en liña: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Algorithmic learning theory, 10th International Conference, ALT'99, Tokyo, Japan, December 1999, proceedings, Osamu Watanabe, Takashi Yokomori (eds.), 1999, New York, Springer, 1 vol. (XI-363 p.), Lecture notes in computer science, 3-540-66748-2 • Algorithmic Learning Theory, Texte imprimé, 9783662165096 |
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| 020 | |a 9783540467694 (PDF) | ||
| 041 | 0 | |a eng | |
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| 100 | 1 | |a Watanabe, Osamu. | |
| 245 | 1 | 0 | |a Algorithmic learning theory : |b 10th International Conference, ALT 99, Tokyo, Japan, December 6-8, 1999 : proceedings |c [edited by] Osamu Watanabe, Takashi Yokomori. |
| 260 | |a Berlin [etc.] : |b Springer. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Lecture notes in computer science. Lecture notes in artificial intelligence |v 1720 |x 1611-3349 |x 2945-9141 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a Invited Lectures -- Tailoring Representations to Different Requirements -- Theoretical Views of Boosting and Applications -- Extended Stochastic Complexity and Minimax Relative Loss Analysis -- Regular Contributions -- Algebraic Analysis for Singular Statistical Estimation -- Generalization Error of Linear Neural Networks in Unidentifiable Cases -- The Computational Limits to the Cognitive Power of the Neuroidal Tabula Rasa -- The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract) -- The VC-Dimension of Subclasses of Pattern Languages -- On the V ? Dimension for Regression in Reproducing Kernel Hilbert Spaces -- On the Strength of Incremental Learning -- Learning from Random Text -- Inductive Learning with Corroboration -- Flattening and Implication -- Induction of Logic Programs Based on ?-Terms -- Complexity in the Case Against Accuracy: When Building One Function-Free Horn Clause Is as Hard as Any -- A Method of Similarity-Driven Knowledge Revision for Type Specializations -- PAC Learning with Nasty Noise -- Positive and Unlabeled Examples Help Learning -- Learning Real Polynomials with a Turing Machine -- Faster Near-Optimal Reinforcement Learning: Adding Adaptiveness to the E3 Algorithm -- A Note on Support Vector Machine Degeneracy -- Learnability of Enumerable Classes of Recursive Functions from Typical Examples -- On the Uniform Learnability of Approximations to Non-recursive Functions -- Learning Minimal Covers of Functional Dependencies with Queries -- Boolean Formulas Are Hard to Learn for Most Gate Bases -- Finding Relevant Variables in PAC Model with Membership Queries -- General Linear Relations among Different Types of Predictive Complexity -- Predicting Nearly as Well as the Best Pruning of a Planar Decision Graph -- On Learning Unionsof Pattern Languages and Tree Patterns. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 650 | |a Informatique | ||
| 650 | |a Apprentissage automatique | ||
| 650 | |a Algorithmes | ||
| 650 | |a Intelligence artificielle | ||
| 650 | |a Logique symbolique et mathématique | ||
| 650 | |a Actes de congrès | ||
| 700 | 1 | |a Yokomori, Takashi. |4 pbd | |
| 711 | 2 | |a Algorithmic learning theory |n (10 |d :1999 |c :Tokyo). |4 aut | |
| 776 | 0 | |0 049040111 |t Algorithmic learning theory |o 10th International Conference, ALT'99, Tokyo, Japan, December 1999 |o proceedings |f Osamu Watanabe, Takashi Yokomori (eds.) |d 1999 |c New York |n Springer |p 1 vol. (XI-363 p.) |s Lecture notes in computer science |z 3-540-66748-2 | |
| 776 | 0 | |t Algorithmic Learning Theory |b Texte imprimé |z 9783662165096 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/3-540-46769-6 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-WZ4798PC-R |z Accès sur la plateforme Istex | |
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