20 January 2023
Inference in Structured High-Dimensional Modelsonline course
The course offers a general approach to draw inference in many high-dimensional models with various hidden structures. We develop a general framework for model+structure combinations and within this framework study various statistical problems such as estimation problem, posterior contraction problem, uncertainty quantification and structure recovery. The proposed general framework unifies a very broad class of high-dimensional models and structures, interesting and important in their own right.
E. N. Belitser is an associate professor at the Department of Mathematics at VU, specializing in mathematical statistics.
This course is suitable for anybody with a strong interest in mathematical statistics, and preference for mathematical preciseness. Especially PhD candidates and master students at the final year, dealing with high-dimensional models, uncertainty quantification and Bayesian methodology can benefit from this course.
A strong background in mathematical statistics and probability is recommended.
By the end of this course, students will:
be familiarized with the new notions of modern high-dimensional statistics and empirical Bayes methodology,
be acquainted with the deceptiveness phenomenon in uncertainty quantification problem,
have learnt and understood a general approach to tackle a big family of combinations: high-dimensional model + structure,
have practiced how to apply the general approach to concrete combination model + structure.
EUR 800: -Students, PhD students and employees of VU Amsterdam: €500
-Students and PhD students: €600
Applications received before 15 October €50 receive Early Bird Discount
We offer an Equal Access Scholarship. Deadline 15 November. Find out more via www.vu.nl/winterschool