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Statistics Seminar, "Probabilistic Independence, Graphs, and Random Networks", Kayvan Sadeghi, Dept of Pure Mathematics and Mathematical Statistics, University of Cambridge

Tid: 2018-04-06 13:15 till 14:00 Seminarium

The main purpose of this talk is to explore the relationship between the 
set of conditional independence statements induced by a probability 
distribution and the set of separations induced by graphs as studied in 
graphical models. I introduce the concepts of Markov property and 
faithfulness, and provide conditions under which a given probability 
distribution is Markov or faithful to a graph in a general setting. I 
discuss the implications of these conditions in devising structural 
learning algorithms, in understanding exchangeabile vectors, and in 
random network analysis.

Om händelsen
Tid: 2018-04-06 13:15 till 14:00


dragi [at] maths [dot] lth [dot] se

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Sidansvarig: webbansvarig@math.lu.se | 2017-05-23