Inductive Logic Programming 13th International Conference, ILP 2003, Szeged, Hungary, September 29 - October 1, 2003, Proceedings
Other Authors: | , |
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Format: | eBook |
Language: | English |
Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2003, 2003
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Edition: | 1st ed. 2003 |
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:
- Invited Papers
- A Personal View of How Best to Apply ILP
- Agents that Reason and Learn
- Research Papers
- Mining Model Trees: A Multi-relational Approach
- Complexity Parameters for First-Order Classes
- A Multi-relational Decision Tree Learning Algorithm – Implementation and Experiments
- Applying Theory Revision to the Design of Distributed Databases
- Disjunctive Learning with a Soft-Clustering Method
- ILP for Mathematical Discovery
- An Exhaustive Matching Procedure for the Improvement of Learning Efficiency
- Efficient Data Structures for Inductive Logic Programming
- Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
- On Condensation of a Clause
- A Comparative Evaluation of Feature Set Evolution Strategies for Multirelational Boosting
- Comparative Evaluation of Approaches to Propositionalization
- Ideal Refinement of Descriptions in -Log
- Which First-Order Logic Clauses Can Be Learned Using Genetic Algorithms?
- Improved Distances for Structured Data
- Induction of Enzyme Classes from Biological Databases
- Estimating Maximum Likelihood Parameters for Stochastic Context-Free Graph Grammars
- Induction of the Effects of Actions by Monotonic Methods
- Hybrid Abductive Inductive Learning: A Generalisation of Progol
- Query Optimization in Inductive Logic Programming by Reordering Literals
- Efficient Learning of Unlabeled Term Trees with Contractible Variables from Positive Data
- Relational IBL in Music with a New Structural Similarity Measure
- An Effective Grammar-Based Compression Algorithm for Tree Structured Data