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...
| Other Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
1997, 1997
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| Edition: | 1st ed. 1997 |
| Series: | Lecture Notes in Artificial Intelligence
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| Subjects: | |
| 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