Machine Learning: ECML'97 9th European Conference on Machine Learning, Prague, Czech Republic, April 23 - 25, 1997, Proceedings

This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 revised full papers selected from a total of 73 submissions. Also included are an abstract and two papers corresponding...

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Bibliographic Details
Other Authors: Someren, Maarten van (Editor), Widmer, Gerhard (Editor)
Format: eBook
Published: Berlin, Heidelberg Springer Berlin Heidelberg 1997, 1997
Edition:1st ed. 1997
Series:Lecture Notes in Artificial Intelligence
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • Uncertain learning agents
  • Constructing and sharing perceptual distinctions
  • On prediction by data compression
  • Induction of feature terms with INDIE
  • Exploiting qualitative knowledge to enhance skill acquisition
  • Integrated learning and planning based on truncating temporal differences
  • ?-subsumption for structural matching
  • Classification by Voting Feature Intervals
  • Constructing intermediate concepts by decomposition of real functions
  • Conditions for Occam's razor applicability and noise elimination
  • Learning different types of new attributes by combining the neural network and iterative attribute construction
  • Metrics on terms and clauses
  • Learning when negative examples abound
  • A model for generalization based on confirmatory induction
  • Learning Linear Constraints in Inductive Logic Programming
  • Finite-Element methods with local triangulation refinement for continuous reinforcement learning problems
  • Learning in dynamically changing domains: Theory revision and context dependence issues
  • Inductive Genetic Programming with Decision Trees
  • Parallel anddistributed search for structure in multivariate time series
  • Compression-based pruning of decision lists
  • Probabilistic Incremental Program Evolution: Stochastic search through program space
  • NeuroLinear: A system for extracting oblique decision rules from neural networks
  • Inducing and using decision rules in the GRG knowledge discovery system
  • Learning and exploitation do not conflict under minimax optimality
  • Model combination in the multiple-data-batches scenario
  • Search-based class discretization
  • Natural ideal operators in Inductive Logic Programming
  • A case study in loyalty and satisfaction research
  • Ibots learn genuine team solutions
  • Global data analysis and the fragmentation problem in decision tree induction
  • Case-based learning: Beyond classification of feature vectors
  • Empirical learning of Natural Language Processing tasks
  • Human-Agent Interaction and Machine Learning