Research Group "Stochastic Algorithms and Nonparametric Statistics"
Seminar "Modern Methods in Applied Stochastics and Nonparametric
Statistics" Summer Semester 2013
| Place: |
Weierstrass-Institute for Applied Analysis and Stochastics
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Room 406 (4th floor), Mohrenstraße 39, 10117 Berlin |
| Time: |
Tuesdays, 3.00 p.m. - 4.00 p.m. |
| Wednesday, 03.04.13 |
First Talk: Mirjam Blum (Universität Siegen) |
| 13:30 - 14:30 im ESH: |
A short introduction into a few aspects of environmental physics and geomathematics |
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Second Talk: Dr. Roland Hildebrand (Université Joseph Fourier, Grenoble) |
| 15:30 - 16:30 im ESH: |
Konvexe Optimierung und semi-definite Relaxierungen |
| 09.04.13 |
No seminar! |
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| Monday, 15.04.13 |
Dr. Andrea Fuster (TU Eindhoven) |
| 11:00 - 12:00 im ESH: |
Riemannian framework for brain diffusion MRI |
| 23.04.13 |
No seminar! |
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| 30.04.13 |
Dr. Alexander Goldenshluger |
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A unified framework for change point detection and other related problems
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| 07.05.13 |
Marcel Ladkau (WIAS Berlin) |
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A new multi-factor stochastic volatility model with displacement |
| 14.05.13 |
Mathias Trabs (HU Berlin) |
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Semiparametric efficiency for inverse problems with applications to deconvolution and Lévy models |
| 21.05.13 |
Alexander Gasnikov (MIPT, Moscow, Russia) |
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Sparsity page rank |
| 28.05.13 |
Elmar Diederichs (MIPT, Moscow, Russia) |
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Identifying enterotypes by high dimensional clustering |
| 04.06.13 |
tba |
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tba |
| 11.06.13 |
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| 18.06.13 |
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| 25.06.13 |
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| 02.07.13 |
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| 09.07.13 |
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| 16.07.13 |
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| 23.07.13 |
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last reviewed: April, 24, 2013, Karsten Tabelow
15.04.13 (Monday!)
Name: Dr. Andrea Fuster
Titel: Riemannian framework for brain diffusion MRI
Abstract: One of the approaches in the analysis of brain diffusion
MRI data is to consider white matter as a Riemannian manifold, with a metric related to the diffusion tensor.
In this framework geodesic tractography can be performed to infer the architecture of white matter pathways in the brain.
We propose a novel Riemannian metric and present promising tractography results.
30.04.2013
Dr. Alexander Goldenshluger
A unified framework for change point detection and other related problems
Abstract: We propose a unified convex-optimization-based framework for problems of detecting a
signal of a given shape in Gaussian noise. The framework covers various detection settings
including: detection of jumps in curves and their derivatives; detection of a periodic component
in Gaussian time series; and signal detection from indirect observations. We present a general
detection procedure, analyze its properties and show that it cannot be improved in some specific
settings.
07.05.2013
Marcel Ladkau (WIAS Berlin)
A new multi-factor stochastic volatility model with displacement
Abstract:
tba
14.05.2013
Mathias Trabs (HU Berlin)
Semiparametric efficiency for inverse problems with applications to deconvolution and Lévy models
Abstract: Starting with a linear inverse problem in an abstract white noise model,
we study semiparametric efficiency in the sense of Hájek-Le Cam. The
inverse problem embeds into a general setup where a convolution theorem is
obtained. The local behavior of the model is described by the score
operator. The results are then applied to a deconvolution setting and to
the nonlinear inverse problem in a Lévy model. In the latter we observe
a Lévy process at low frequency and we determine the information bound
for linear functionals of the jump density. Of particular interest is the
estimation of the distribution function in both settings. Locally the
deconvolution model and the Lévy model converge to limit experiments
which are given by a white noise inverse problem with an appropriate
linear operator. The lower bounds coincide with recent results on the
asymptotic variance of estimators in both models.
21.05.2013
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28.05.2013
Niklas Willrich (WIAS Berlin)
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04.06.2013
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