Seminar on Computational Learning and
Adaptation
Knowledge Acquisition using Relational Learning
Ichise Ryutaro
Center for the Study of Language and Information
and Intelligent Systems Research Division, National Institute of Informatics
ichise@csli.stanford.edu
Relational learning is a widely used technique to acquire structured
concepts from collections of data. Two approaches to acquire concepts
represented in first order logic are inductive logic programming (ILP)
and genetic programming (GP). These two approaches are very similar in
terms of their methods and goals, yet their combination in previous
work is rare. In this talk, we introduce an approach that synthesizes
inductive logic programming and genetic programming. We also look at
applications of this approach, especially to acquire knowledge in time
series data.
Date: Thursday, October 11
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Time: 4:15-5:30PM
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Place: Cordura 100
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