Algorithmic learning theory : 10th International Conference, ALT '99, Tokyo, Japan, December 6-8, 1999 : proceedings

Osamu Watanabe, Takashi Yokomori (eds.)

This book constitutes the refereed proceedings of the 10th International Conference on Algorithmic Learning Theory, ALT'99, held in Tokyo, Japan, in December 1999. The 26 full papers presented were carefully reviewed and selected from a total of 51 submissions. Also included are three invited papers. The papers are organized in sections on Learning Dimension, Inductive Inference, Inductive Logic Programming, PAC Learning, Mathematical Tools for Learning, Learning Recursive Functions, Query Learning and On-Line Learning.

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[目次]

  • 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.

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この本の情報

書名 Algorithmic learning theory : 10th International Conference, ALT '99, Tokyo, Japan, December 6-8, 1999 : proceedings
著作者等 International Workshop on Algorithmic Learning Theory
横森 貴
渡辺 治
Yokomori Takashi
Watanabe Osamu
シリーズ名 Lecture notes in computer science
出版元 Springer
刊行年月 c1999
ページ数 xi, 363 p.
大きさ 24 cm
ISBN 3540667482
NCID BA44377407
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言語 英語
出版国 ドイツ
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