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.05051.1
URN: urn:nbn:de:0030-drops-4303
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2006/430/
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De Raedt, Luc ; Dietterich, Tom ; Getoor, Lise ; Muggleton, Stephen H.

05051 Abstracts Collection -- Probabilistic, Logical and Relational Learning - Towards a Synthesis

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05051_abstracts_collection.430.pdf (0.2 MB)

Abstract

From 30.01.05 to 04.02.05, the Dagstuhl Seminar 05051 ``Probabilistic, Logical and Relational Learning - Towards a 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.05051.1,
  author =	{De Raedt, Luc and Dietterich, Tom and Getoor, Lise and Muggleton, Stephen H.},
  title =	{{05051 Abstracts Collection – Probabilistic, Logical and Relational Learning - Towards a Synthesis}},
  booktitle =	{Probabilistic, Logical and Relational Learning - Towards a Synthesis},
  pages =	{1--27},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5051},
  editor =	{Luc De Raedt and Thomas Dietterich and Lise Getoor and Stephen H. Muggleton},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2006/430},
  URN =		{urn:nbn:de:0030-drops-4303},
  doi =		{10.4230/DagSemProc.05051.1},
  annote =	{Keywords: Statistical relational learning, probabilistic logic learning, inductive logic programming, knowledge representation, machine learning, uncertainty in artificial intelligence}
}

Keywords: Statistical relational learning, probabilistic logic learning, inductive logic programming, knowledge representation, machine learning, uncertainty in
Freie Schlagwörter (deutsch): artificial intelligence
Collection: 05051 - Probabilistic, Logical and Relational Learning - Towards a Synthesis
Issue Date: 2006
Date of publication: 09.02.2006

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