Workshop on Structure Adapting Methods
Berlin, 6-8 November 2009
Registration deadline: October 22, 2009
One possible way out of the curse of dimensionality problem is based on one or another structural assumption which allows to reduce the complexity/dimensionality of the model. A number of such structural assumptions is popular in the statistical literature including single- and multiple-index, additive, models, projection pursuit and sparse models, among many others. Knowing the structure allows for applying the classical methods to the reduced models. Unfortunately, the exact structural information is rarely available and the related problem is to extract the structural information from the data as an important preprocessing step.
The aim of this workshop is bringing together leading specialists from the field of adaptive estimation for discussing the new approaches, ideas, challenges and addressing the algorithmic and mathematical aspects of this new and actively developing area of mathematical statistics and machine learning.
Preliminary list of invited speakers: