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  • Time: Wednesday 10/04/2023 from 11:30 AM to 12:20 PM
  • Location: BLOC 448
  • Pizza and drinks provided

Topic

Graph Matching from a Statistical Perspective

Abstract

Given a pair of networks, graph matching is the problem of finding a correspondence between their vertices. Applications include data de-anonymization, computer vision, language processing, record linkage, and brain connectivity analysis. This talk will present a general overview of the problem, with a focus on some recent methodologies based on the maximum likelihood estimation principle. The talk will focus on computational aspects, theoretical results on graph matchability, and illustrations in simulated and real networks. Finally, some future directions will be discussed.

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