09401 Abstracts Collection – Machine learning approaches to statistical dependences and causality

Janzing, Dominik; Lauritzen, Steffen; Schölkopf, Bernhard

doi:10.4230/DagSemProc.09401.1

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09401 Abstracts Collection – Machine learning approaches to statistical dependences and causality

Authors Dominik Janzing, Steffen Lauritzen, Bernhard Schölkopf

Part of: Volume: Dagstuhl Seminar Proceedings, Volume 9401
Part of: Series: Dagstuhl Seminar Proceedings (DagSemProc)
License: Creative Commons Attribution 4.0 International license
Publication Date: 2010-01-04

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DOI: 10.4230/DagSemProc.09401.1
URN: urn:nbn:de:0030-drops-23636

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Keywords

Machine learning
statistical dependences
causality

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Abstract

From 27.09.2009 to 02.10.2009, the Dagstuhl Seminar 09401 ``Machine learning approaches  to statistical dependences and causality'' was held
in Schloss Dagstuhl~--~Leibniz Center for Informatics.
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.

Cite As Get BibTex

Dominik Janzing, Steffen Lauritzen, and Bernhard Schölkopf. 09401 Abstracts Collection – Machine learning approaches to statistical dependences and causality. In Machine learning approaches to statistical dependences and causality. Dagstuhl Seminar Proceedings, Volume 9401, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010) https://doi.org/10.4230/DagSemProc.09401.1

Author Details

Dominik Janzing

Steffen Lauritzen

Bernhard Schölkopf

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