Probability Seminar

Title: Statistical Analysis of Network Data in the Context of 'Big Data': Large Networks and Many Networks
Speaker: Eric D. Kolaczyk
Speaker Info: Boston University
Brief Description:
Special Note: Note the unusual time for the probability seminar

One of the key challenges in the current era of `Big Data' is the ubiquity of unstructured data, and one particularly prominent example of such data is network data. In this talk we look at two of the ways that network data can be `big': in the sense of networks of many nodes, and in the sense of many networks. Within this context, I will present two vignettes showing how network versions of quite fundamental statistical problems yet remain to be addressed. Specifically, I will touch on the problems of (i) propagation of uncertainty to summary statistics of `noisy' networks, and (ii) estimation and testing for large collections of network data objects. In both cases I will present a formalization of a certain class of problems encountered frequently in practice, describe our work in addressing the core aspects of the problem, and point to some of the many outstanding challenges remaining. At the heart of progress on these problems there likely lies an interesting confluence of concepts and tools from each of mathematics, probability, and statistics.
Date: Monday, May 22, 2017
Time: 3:00PM
Where: Lunt 107
Contact Person: Han Liang Gan
Contact email: ganhl@math.northwestern.edu
Contact Phone:
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