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
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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