Algorithmic learning theory : 9th international conference, ALT &#039,98, Otzenhausen, Germany, October 8-10, 1998 : proceedings

Algorithmic Learning Theory: 9th International Conference, ALT’98 Otzenhausen, Germany, October 8–10, 1998 Proceedings
Author: Michael M. Richter, Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-65013-3
DOI: 10.1007/3-540-49730-7

Table of Contents:

• Editors’ Introduction
• Scalability Issues in Inductive Logic Programming
• Learning to Win Process-Control Games Watching Game-Masters
• Closedness Properties in EX-Identification of Recursive Functions
• Lower Bounds for the Complexity of Learning Half-Spaces with Membership Queries
• Cryptographic Limitations on Parallelizing Membership and Equivalence Queries with Applications to Random Self-Reductions
• Learning Unary Output Two-Tape Automata from Multiplicity and Equivalence Queries
• Computational Aspects of Parallel Attribute-Efficient Learning
• PAC Learning from Positive Statistical Queries
• Structured Weight-Based Prediction Algorithms
• Learning from Entailment of Logic Programs with Local Variables
• Logical Aspects of Several Bottom-Up Fittings
• Learnability of Translations from Positive Examples
• Analysis of Case-Based Representability of Boolean Functions by Monotone Theory
• Locality, Reversibility, and Beyond: Learning Languages from Positive Data
• Synthesizing Learners Tolerating Computable Noisy Data
• Characteristic Sets for Unions of Regular Pattern Languages and Compactness
• Finding a One-Variable Pattern from Incomplete Data
• A Fast Algorithm for Discovering Optimal String Patterns in Large Text Databases
• A Comparison of Identification Criteria for Inductive Inference of Recursive Real-Valued Functions

Includes bibliographical references and index