Computational learning theory : 4th European Conference, EuroCOLT 99, Nordkirchen, Germany, March 29 31, 1999 : proceedings
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| Autor Corporativo: | |
|---|---|
| Outros Autores: | , |
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Colecção: | Lecture notes in computer science. Lecture notes in artificial intelligence
1572 |
| Assuntos: | |
| Acesso em linha: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Computational learning theory, 4th European Conference, EuroCOLT '99, Nordkirchen, Germany, March 29-31 1999, proceedings, Paul Fischer, Hans Ulrich Simon (eds.), 1999, New York, Springer, 1 vol. (X-299 p.), Lecture notes in computer science, 3-540-65701-0 • Computational Learning Theory, Texte imprimé, 9783662208540 |
Sumário:
- Invited Lectures
- Theoretical Views of Boosting
- Open Theoretical Questions in Reinforcement Learning
- Learning from Random Examples
- A Geometric Approach to Leveraging Weak Learners
- Query by Committee, Linear Separation and Random Walks
- Hardness Results for Neural Network Approximation Problems
- Learning from Queries and Counterexamples
- Learnability of Quantified Formulas
- Learning Multiplicity Automata from Smallest Counterexamples
- Exact Learning when Irrelevant Variables Abound
- An Application of Codes to Attribute-Efficient Learning
- Learning Range Restricted Horn Expressions
- Reinforcement Learning
- On the Asymptotic Behavior of a Constant Stepsize Temporal-Difference Learning Algorithm
- On-line Learning and Expert Advice
- Direct and Indirect Algorithms for On-line Learning of Disjunctions
- Averaging Expert Predictions
- Teaching and Learning
- On Teaching and Learning Intersection-Closed Concept Classes
- Inductive Inference
- Avoiding Coding Tricks by Hyperrobust Learning
- Mind Change Complexity of Learning Logic Programs
- Statistical Theory of Learning and Pattern Recognition
- Regularized Principal Manifolds
- Distribution-Dependent Vapnik-Chervonenkis Bounds
- Lower Bounds on the Rate of Convergence of Nonparametric Pattern Recognition
- On Error Estimation for the Partitioning Classification Rule
- Margin Distribution Bounds on Generalization
- Generalization Performance of Classifiers in Terms of Observed Covering Numbers
- Entropy Numbers, Operators and Support Vector Kernels.