Horváth / Yamamoto Inductive Logic Programming

13th International Conference, ILP 2003, Szeged, Hungary, September 29 - October 1, 2003, Proceedings
2003
ISBN: 978-3-540-39917-9
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 2835, 406 Seiten, eBook

Reihe: Lecture Notes in Computer Science

Zielgruppe

Research

Autoren/Hrsg.

Horváth, Tamas

Yamamoto, Akihiro

Inhaltsverzeichnis

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.