[Statlist] Next talk: Friday, June 12, 2015 with Ioannis Tsamardinos (Computer Science Department, University of Crete)

[Susanne Kaiser-Heinzmann]

ETH and University of Zurich

Organisers:
Proff. P. Bühlmann - L. Held - T. Hothorn - M. Maathuis -
N. Meinshausen - S. van de Geer - M. Wolf
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We are glad to announce the following talk:

Friday, June 12, 2015 at 15.15h  ETH Zurich HG G 19.1
with Ioannis Tsamardinos (Computer Science Department, University of Crete)                                        

Title:

Advances in Integrative Causal Analysis

Abstract:

Scientific practice typically involves studying a system over a series of studies and data collection, each time trying to unravel a different aspect. In each study, the scientist may take measurements under different experimental conditions and measure different sets of quantities (variables). The result is a collection of heterogeneous data sets coming from different distributions. Even so, these are generated by the same causal mechanism. The general idea in Integrative Causal Analysis (INCA) is to identify the set of causal models that simultaneously fit (are consistent) with all sources of data and prior knowledge and reason with this set of models. Integrative Causal Analysis allows more discoveries than what is possible by independent analysis of datasets. In this talk, we’ll present advances in this direction that lead to algorithms that can handle more types of heterogeneity, and aim at increasing efficiency or robustness of discoveries. Specifically, we’ll present general INCA algorithms for causal discovery from heterogeneous data and proof-of-concept applications and massive evaluation on real data of the main concepts. We'll briefly mention advances for converting the results of tests to posterior probabilities and allow conflict resolution and identification of the confidence network regions, extensions that can deal with prior causal knowledge, and extensions that handle case-control data.

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This abstract is also to be found under the following link: http://stat.ethz.ch/events/research_seminar
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ETH Zürich
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