Algorithmic Learning Theory 10th International Conference, ALT '99 Tokyo, Japan, December 6-8, 1999 Proceedings /
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
1999.
|
| Έκδοση: | 1st ed. 1999. |
| Σειρά: | Lecture Notes in Artificial Intelligence ;
1720 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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 Unions of Pattern Languages and Tree Patterns.
