Algorithmic learning theory : 7th International Workshop, ALT '96, Sydney, Australia, October 23-25, 1996 : proceedings
This book constitutes the refereed proceedings of the 7th International Workshop on Algorithmic Learning Theory, ALT '96, held in Sydney, Australia, in October 1996. The 16 revised full papers presented were selected from 41 submissions; also included are eight short papers as well as four full...
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| Formaat: | Livre numérique |
| Taal: | Anglais |
| Gepubliceerd in: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Reeks: | Lecture notes in computer science. Lecture notes in artificial intelligence
1160 |
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| Online toegang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Algorithmic learning theory, 7th international workshop, ALT '96, Sydney, Australia, October 23-25, 1996, proceedings, Arun K. Sharma, Setsuo Arikawa, eds, 1996, New York, Springer, 1 vol. (XVII-336 p.), Lecture notes in computer science, 3-540-61863-5 • Algorithmic Learning Theory, Texte imprimé, 9783662188941 |
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| 100 | 1 | |a Arikawa, Setsuo, |d 1941- | |
| 245 | 1 | 0 | |a Algorithmic learning theory : |b 7th International Workshop, ALT '96, Sydney, Australia, October 23-25, 1996 : proceedings |c [edited by] Setsuo Arikawa, Arun K. Sharma. |
| 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 1160 |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 Managing complexity in neuroidal circuits -- Learnability of exclusive-or expansion based on monotone DNF formulas -- Improved bounds about on-line learning of smooth functions of a single variable -- Query learning of bounded-width OBDDs -- Learning a representation for optimizable formulas -- Limits of exact algorithms for inference of minimum size finite state machines -- Genetic fitness optimization using rapidly mixing Markov chains -- The kindest cut: Minimum message length segmentation -- Reducing complexity of decision trees with two variable tests -- The complexity of exactly learning algebraic concepts -- Efficient learning of real time two-counter automata -- Cost-sensitive feature reduction applied to a hybrid genetic algorithm -- Effects of Feature Selection with Blurring on neurofuzzy systems -- Boosting first-order learning -- Incorporating hypothetical knowledge into the process of inductive synthesis -- Induction of Constraint Logic Programs -- Constructive learning of translations based on dictionaries -- Inductive logic programming beyond logical implication -- Noise elimination in inductive concept learning: A case study in medical diagnosis -- MML estimation of the parameters of the spherical fisher distribution -- Learning by erasing -- On learning and co-learning of minimal programs -- Inductive inference of unbounded unions of pattern languages from positive data -- A class of prolog programs inferable from positive data -- Vacillatory and BC learning on noisy data -- Transformations that preserve learnability -- Probabilistic limit identification up to small sets -- Reflecting inductive inference machines and its improvement by therapy. | |
| 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 | ||
| 520 | |a This book constitutes the refereed proceedings of the 7th International Workshop on Algorithmic Learning Theory, ALT '96, held in Sydney, Australia, in October 1996. The 16 revised full papers presented were selected from 41 submissions; also included are eight short papers as well as four full length invited contributions by Ross Quinlan, Takeshi Shinohara, Leslie Valiant, and Paul Vitanyi, and an introduction by the volume editors. The book covers all areas related to algorithmic learning theory, ranging from theoretical foundations of machine learning to applications in several areas. | ||
| 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 Sharma, Arun K., |d 1962-...., |c auteur en mathématiques. |4 pbd | |
| 711 | 2 | |a Algorithmic learning theory |n (07 |d :1996 |c :Sydney, Australie). |4 aut | |
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| 776 | 0 | |t Algorithmic Learning Theory |b Texte imprimé |z 9783662188941 | |
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