Matrix Estimation Meets Statistical Network Analysis: Extracting low-dimensional structures in high dimension
Florentina Bunea
Cornell University, Ithaca, USAAngelika Rohde
Universität Freiburg, GermanyPatrick Wolfe
Purdue University, West Lafayette, USAHarrison H. Zhou
Yale University, New Haven, USA
Abstract
The study of complex relationships among the elements of a large collection of random variables lead to the development of a number of areas in probability and statistics such as probabilistic network analysis or random matrix theory. The aim of the workshop was to address the challenge to develop a coherent mathematical framework within which these areas can be integrated, for a successful analysis of massive and complicated data sets.
Cite this article
Florentina Bunea, Angelika Rohde, Patrick Wolfe, Harrison H. Zhou, Matrix Estimation Meets Statistical Network Analysis: Extracting low-dimensional structures in high dimension. Oberwolfach Rep. 15 (2018), no. 2, pp. 1745–1783
DOI 10.4171/OWR/2018/29