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Spezialvorlesung "Logic and Learning"
Prof. Dr. Luc De Raedt
Co-organizer: Dipl.-Inf. K. Kersting, Dipl.-Inf. A. Zimmermann
Credit points: 3
Thursday, 11-13 o'clock, SR 101-00-010/014
This course will provide a gentle introduction into the field
of logic and learning. This field is also known under the names
of inductive logic programming, relational learning and multi-relational
data mining.
It essentially studies machine learning and data mining
using rich representations, such as first order logic, graphs, trees,
etc.
It has received quite some attention over the past ten to fifteen years
and is also among the core research areas of the machine learning lab in
Freiburg.
The course will start by providing an overview of different
representations
for machine learning and data mining, with an emphasis on logical
representations.
It will then study in detail how to use these representations for
describing
machine learning and data mining problems, and also show how existing
machine learning
and data mining algorithms can be adapted to work with these
representations.
The course will be centered around a book that the lecturer is preparing
around the topic.
Slides :
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