|Talks|

Network models, sampling, and symmetry properties

Visiting speaker
Past Talk
Peter Orbanz
Associate Professor, Columbia University
Jan 16, 2019
10:30 am
Jan 16, 2019
10:30 am
In-person
4 Thomas More St
London E1W 1YW, UK
The Roux Institute
Room
100 Fore Street
Portland, ME 04101
Network Science Institute
2nd floor
Network Science Institute
11th floor
177 Huntington Ave
Boston, MA 02115
Network Science Institute
2nd floor
Room
58 St Katharine's Way
London E1W 1LP, UK

Talk recording

A recent body of work, by myself and many others, aims to develop a statistical theory of network data for problems a single network is observed. Of the models studied in this area, graphon models are probably most widely known in statistics. I will explain the relationship between three aspects of this work: (1) Specific models, such as graphon models, graphex models, and edge-exchangeable graphs. (2) Sampling theory for networks, specifically in the case statisticians might refer to as an infinite-population limit. (3) Invariance properties, especially various forms of exchangeability. I will also present recent results that show how statistically relevant results (such as central limit theorems) can be derived from such invariance properties.

About the speaker
Peter Orbanz is associate professor of statistics at Columbia University. His research interests include network and relational data, Bayesian nonparametrics, symmetry principles in machine learning and statistics, and hierarchies of latent variables. He was an undergraduate student at the University of Bonn, a PhD student at ETH Zurich, and a postdoctoral fellow at the University of Cambridge.
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Jan 16, 2019