License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.07161.1
URN: urn:nbn:de:0030-drops-13885
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1388/
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De Raedt, Luc ; Dietterich, Thomas ; Getoor, Lise ; Kersting, Kristian ; Muggleton, Stephen H.

07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis

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07161_abstracts_collection.1388.pdf (0.2 MB)

Abstract

From April 14 -- 20, 2007, the Dagstuhl Seminar 07161 ``Probabilistic, Logical and Relational Learning - A Further Synthesis'' was held
in the International Conference and Research Center (IBFI),
Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available.

BibTeX - Entry

@InProceedings{deraedt_et_al:DagSemProc.07161.1,
  author =	{De Raedt, Luc and Dietterich, Thomas and Getoor, Lise and Kersting, Kristian and Muggleton, Stephen H.},
  title =	{{07161 Abstracts Collection – Probabilistic, Logical and Relational Learning - A Further Synthesis}},
  booktitle =	{Probabilistic, Logical and Relational Learning - A Further Synthesis},
  pages =	{1--21},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{7161},
  editor =	{Luc de Raedt and Thomas Dietterich and Lise Getoor and Kristian Kersting and Stephen H. Muggleton},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2008/1388},
  URN =		{urn:nbn:de:0030-drops-13885},
  doi =		{10.4230/DagSemProc.07161.1},
  annote =	{Keywords: Artificial Intelligence, Uncertainty in AI, Probabilistic Reasoning, Knowledge Representation, Logic Programming, Relational Learning, Inductive Logic Programming, Graphical Models, Statistical Relational Learning, First-Order Logical and Relational Probabilistic Languages}
}

Keywords: Artificial Intelligence, Uncertainty in AI, Probabilistic Reasoning, Knowledge Representation, Logic Programming, Relational Learning, Inductive Logic
Freie Schlagwörter (englisch): Programming, Graphical Models, Statistical Relational Learning, First-Order Logical and Relational Probabilistic Languages
Collection: 07161 - Probabilistic, Logical and Relational Learning - A Further Synthesis
Issue Date: 2008
Date of publication: 07.03.2008

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