Matrix Estimation Meets Statistical Network Analysis: Extracting low-dimensional structures in high dimension
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...
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Veröffentlicht in: | Oberwolfach reports 2019-04, Vol.15 (2), p.1745-1783 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | 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. |
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ISSN: | 1660-8933 1660-8941 |
DOI: | 10.4171/OWR/2018/29 |