• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • А
  • А
  • А
  • А
  • А
Обычная версия сайта

Новости

Прошла Международная Конференция "Nonparametric and high-dimensional statistics" в г. Гейдельберг, Германия

20-21 июля прошла Международная Конференция "Nonparametric and high-dimensional statistics" в г. Гейдельберг, Германия,  организованная Международной Лабораторией стохастического анализа и его приложений совместно с MAThematics Center Heidelberg.

Workshop organized by the Research Training Group "Statistical Modeling of Complex Systems and Processes” Heidelberg / Mannheim in cooperation with the International Laboratory of Stochastic Analysis and its Applications Higher School of Economics, Moscow and MAThematics Center Heidelberg (MATCH)

ORGANIZERS: Valentin Konakov, Enno Mammen, Alexandre Tsybakov

The workshop will be held in Heidelberg on 20 July 2015 in the guesthouse seminar room (INF 370/371). Directions to the University of Heidelberg Guesthouse.

 Workshop Programme (PDF, 65 Кб)

 SPEAKERS

 

Harrison Zhou, Yale University
Title: Sparse Canonical Correlation Analysis: Minimaxity, Adaptivity, and Computational Barriers

Denis Belomestny, University of Duisburg-Essen
Title: Low-rank diffusion covariance matrix estimation under presence of jumps

Karl Gregory, University of Mannheim
Title: Pointwise inference in the high-dimensional additive model

Guillaume Lecue, Ecole Polytechnique, University Paris Saclay, France
Title: Estimation properties of regularization methods under the small ball property

Pierre Bellec, ENSAE ParisTech - University Paris Saclay, France
Title: Aggregation of supports along the Lasso path in linear regression

Vladimir Panov, National Research University, Higher School of Economics, Moscow, Russia
Title: Semiparametric estimation in the normal variance-mean mixture model

Claudia Strauch, Heidelberg University
Title: On nonparametric adaptive density estimation for ergodic diffusions in higher dimensions

Alexandre Tsybakov, ENSAE ParisTech, France
Title: Oracle inequalities for network models and sparse graphon estimation