Algorithmic Learning Theory: 11th International Conference, ALT 2000 Sydney, Australia, December 11–13, 2000 Proceedings

William W. Cohen (auth.), Hiroki Arimura, Sanjay Jain, Arun Sharma (eds.)3540412379, 9783540412373

This book constitutes the refereed proceedings of the 11th International Conference on Algorithmic Learning Theory, ALT 2000, held in Sydney, Australia in December 2000.
The 22 revised full papers presented together with three invited papers were carefully reviewed and selected from 39 submissions. The papers are organized in topical sections on statistical learning, inductive logic programming, inductive inference, complexity, neural networks and other paradigms, support vector machines.

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Table of contents :
Extracting Information from the Web for Concept Learning and Collaborative Filtering….Pages 1-12
The Divide-and-Conquer Manifesto….Pages 13-26
Sequential Sampling Techniques for Algorithmic Learning Theory….Pages 27-40
Average-Case Analysis of Classification Algorithms for Boolean Functions and Decision Trees….Pages 194-208
Self-duality of Bounded Monotone Boolean Functions and Related Problems….Pages 209-223
Sharper Bounds for the Hardness of Prototype and Feature Selection….Pages 224-238
On the Hardness of Learning Acyclic Conjunctive Queries….Pages 238-251
Dynamic Hand Gesture Recognition Based On Randomized Self-Organizing Map Algorithm….Pages 252-263
On Approximate Learning by Multi-layered Feedforward Circuits….Pages 264-278
Towards an Algorithmic Statistics….Pages 41-55
Minimum Message Length Grouping of Ordered Data….Pages 56-70
Learning From Positive and Unlabeled Examples….Pages 71-85
Learning Erasing Pattern Languages with Queries….Pages 86-100
Learning Recursive Concepts with Anomalies….Pages 101-115
Identification of Function Distinguishable Languages….Pages 116-130
A Probabilistic Identification Result….Pages 131-141
A New Framework for Discovering Knowledge from Two-Dimensional Structured Data Using Layout Formal Graph System….Pages 141-155
Hypotheses Finding via Residue Hypotheses with the Resolution Principle….Pages 156-165
Conceptual Classifications Guided by a Concept Hierarchy….Pages 166-178
Learning Taxonomic Relation by Case-based Reasoning….Pages 179-193
The Last-Step Minimax Algorithm….Pages 279-290
Rough Sets and Ordinal Classification….Pages 291-305
A note on the generalization performance of kernel classifiers with margin….Pages 306-315
On the Noise Model of Support Vector Machines Regression….Pages 316-324
Computationally Efficient Transductive Machines….Pages 325-337