Dear all,

It is my pleasure to announce the following CWI Machine Learning seminar

Speaker:  Martin Larsson (Carnegie Mellon University) Title:    E-variables for hypotheses generated by constraints Date:     Monday 10 March, 10:30 Location: CWI L016

Please find the abstract below.

Hope to see you then.

Best wishes,

Wouter

Details:

https://www.cwi.nl/en/groups/machine-learning/events/machine-learning-semina...

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*Title:* E-variables for hypotheses generated by constraints

*Abstract: *There is a natural convex duality relationship between a statistical hypothesis and its set of e-variables. If the hypothesis is defined through a collection of linear constraints, often understood as (generalized) moment restrictions, then one expects that any e-variable can be expressed in terms of convex combinations of the constraint functions. In simple situations, such as for finite sample spaces, results of this kind can be proved by convex duality in Euclidean space. However, in more general cases the situation is less clear. In this talk I will show that e-variable representations of the kind described above hold in arbitrary sample spaces, without any regularity conditions or other assumptions whatsoever. I will also discuss a number of examples illustrating how the abstract theory instantiates in concrete cases.