One of the greatest advantages of representing data with graphs is access to generic algorithms for analytic tasks, such as clustering. In this talk, Dr. Schramm will describe some popular graph clustering algorithms, and explain why they are well-motivated from a theoretical perspective. The slides from this presentation can be viewed here.
Presented by GraphXD and BIDS at the University of California, Berkeley, on Thursday, September 28, 2017.
Graphs Across Domains (GraphXD) is a BIDS working group that connects scientists, researchers, and theorists interested in graphs (networks) from a variety of fields (including mathematics, computer science, biology, physics, economics, and sociology) through seminars and workshops.