Algorithmic Learning Theory : 8th International Workshop, ALT '97, Sendai, Japan, October 6-8, 1997. Proceedings / edited by Ming Li, Akira Maruoka.

Format:

Book

Contributor:

Li, Ming, 1955 July 16- editor.

Maruoka, Akira, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 1316.

Lecture Notes in Artificial Intelligence ; 1316

Language:

English

Subjects (All):

Artificial intelligence.

Logic, Symbolic and mathematical.

Artificial Intelligence.

Mathematical Logic and Formal Languages.

Local Subjects:

Artificial Intelligence.

Mathematical Logic and Formal Languages.

Physical Description:

1 online resource (XIV, 470 pages).

Edition:

First edition 1997.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1997.

System Details:

text file PDF

Summary:

This book constitutes the refereed proceedings of the 8th International Workshop on Algorithmic Learning Theory, ALT'97, held in Sendai, Japan, in October 1997. The volume presents 26 revised full papers selected from 42 submissions. Also included are three invited papers by leading researchers. Among the topics addressed are PAC learning, learning algorithms, inductive learning, inductive inference, learning from examples, game-theoretical aspects, decision procedures, language learning, neural algorithms, and various other aspects of computational learning theory.

Contents:

Program error detection/correction: Turning PAC learning into Perfect learning

Team learning as a game

Inferability of recursive real-valued functions

Learning of R.E. Languages from good examples

Identifiability of subspaces and homomorphic images of zero-reversible languages

On exploiting knowledge and concept use in learning theory

Partial occam's razor and its applications

Derandomized learning of boolean functions

Learning DFA from simple examples

PAC learning under helpful distributions

PAC learning using Nadaraya-Watson estimator based on orthonormal systems

Monotone extensions of boolean data sets

Classical Brouwer-Heyting-Kolmogorov interpretation

Inferring a system from examples with time passage

Polynomial time inductive inference of regular term tree languages from positive data

Synthesizing noise-tolerant language learners

Effects of Kolmogorov complexity present in inductive inference as well

Learning one-variable pattern languages very efficiently on average, in parallel, and by asking queries

Oracles in ? 2 p are sufficient for exact learning

Exact learning via teaching assistants (Extended abstract)

An efficient exact learning algorithm for ordered binary decision diagrams

Probability theory for the Brier game

Learning and revising theories in noisy domains

A note on a scale-sensitive dimension of linear bounded functionals in Banach Spaces

On the relevance of time in neural computation and learning

A simple algorithm for predicting nearly as well as the best pruning labeled with the best prediction values of a decision tree

Learning disjunctions of features

Learning simple deterministic finite-memory automata

Learning acyclic first-order horn sentences from entailment

On learning disjunctions of zero-one threshold functions with queries.

Other Format:

Printed edition:

ISBN:

978-3-540-69602-5

9783540696025

Access Restriction:

Restricted for use by site license.