Computational Learning Theory : 4th European Conference, EuroCOLT'99 Nordkirchen, Germany, March 29-31, 1999 Proceedings / edited by Paul Fischer, Hans U. Simon.

Format:

Book

Contributor:

Fischer, Paul, 1956- editor.

Simon, Hans U., editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 1572.

Lecture Notes in Artificial Intelligence ; 1572

Language:

English

Subjects (All):

Artificial intelligence.

Pattern perception.

Logic, Symbolic and mathematical.

Algorithms.

Computers.

Artificial Intelligence.

Pattern Recognition.

Mathematical Logic and Formal Languages.

Algorithm Analysis and Problem Complexity.

Computation by Abstract Devices.

Local Subjects:

Artificial Intelligence.

Pattern Recognition.

Mathematical Logic and Formal Languages.

Algorithm Analysis and Problem Complexity.

Computation by Abstract Devices.

Physical Description:

1 online resource (X, 299 pages).

Edition:

First edition 1999.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1999.

System Details:

text file PDF

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-540-49097-5

9783540490975

Access Restriction:

Restricted for use by site license.