Mathematical Statistics Seminar

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Speaker(s): 
Jean-Pierre Florens (U Toulouse)
Date: 
Wednesday, February 14, 2018 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

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Speaker(s): 
Elisabeth Gassiat (Université Paris-Sud)
Date: 
Wednesday, January 31, 2018 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

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Speaker(s): 
Anthony Nouy (Nantes)
Date: 
Wednesday, January 17, 2018 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

Nonparametric density estimation for intentionally corrupted functional data

Speaker(s): 
Alexander Meister (Universität Rostock)
Date: 
Wednesday, December 6, 2017 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

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Speaker(s): 
Gitta Kotyniok (TU Berlin)
Date: 
Wednesday, November 29, 2017 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

On the Exponentially Weighted Aggregate with the Laplace Prior

Speaker(s): 
Arnak Dalayan (ENSAE Paris)
Date: 
Wednesday, November 8, 2017 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

In this talk, we will present some results on the statistical behaviour of the Exponentially Weighted Aggregate (EWA) in the problem of high-dimensional regression with fixed design. Under the assumption that the underlying regression vector is sparse, it is reasonable to use the Laplace distribution as a prior.

Statistical inference for McKean-Vlasov-SDEs

Speaker(s): 
Denis Belomestny (Universität Duisburg-Essen)
Date: 
Wednesday, November 1, 2017 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

McKean-Vlasov-SDEs provide a very rich modelling framework for large complex systems. They naturally appear in modelling and simulation of turbulent flows by fluid-particle method. In biomathematics, a McKean-Vlasov-SDE model for neuronal networks has been proposed. Although potentially very powerful, the lack of efficient statistical procedures prevents further expansion of these results into application areas. When proposing a McKean-Vlasov-SDE model, one of the main challenges is the appropriate choice of the coefficients.

Two-sample Hypothesis Testing for Inhomogeneous Random Graphs

Speaker(s): 
Debarghya Ghoshdastidar (Universität Tübingen)
Date: 
Wednesday, October 25, 2017 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

In this talk, we consider the problem of testing between two populations of inhomogeneous random graphs defined on the same set of vertices. We are particularly interested in the high-dimensional setting where the population size is potentially much smaller than the graph size, and may even be constant. It is known that this setting cannot be tackled if the separation between two models is quantified in terms of total variation distance.

Big ball probability with applications in statistical inference

Speaker(s): 
Vladimir Spokoiny (WIAS Berlin)
Date: 
Wednesday, October 18, 2017 - 10:00am
Location: 
WIAS, Erhard-Schmidt-Saal, Mohrenstraße 39, 10117 Berlin

We derive the bounds on the Kolmogorov distance between probabilities of two Gaussian elements to hit a ball in a Hilbert space. The key property of these bounds is that they are dimensional-free and depend on the nuclear (Schatten-one) norm of the difference between the covariance operators of the elements. We are also interested in the anticoncentration bound for a squared norm of a non-centered Gaussian element in a Hilbert space. All bounds are sharp and cannot be improved in general.

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