Matrix Estimation Meets Statistical Network Analysis: Extracting low-dimensional structures in high dimension

  • Florentina Bunea

    Cornell University, Ithaca, USA
  • Angelika Rohde

    Universität Freiburg, Germany
  • Patrick Wolfe

    Purdue University, West Lafayette, USA
  • Harrison 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