February 9, 2021

eTALK | Recent Advances in Dense Subgraph Discovery | Ass. Prof. Ch. Tsourakakis

Invited speaker Charalampos Tsourakakis, Assistant Professor in Computer Science at Boston University, will give a talk on Recent Advances in Dense Subgraph Discovery, on Wednesday 24 February, at 14.00.

Abstract

Finding dense subgraphs in large-scale networks is an important graph mining problem with numerous applications, including anomaly detection in security, community detection in social networks, and mining the Web graph. In this talk I will present recent advances related to the well-studied densest subgraph problem (DSP). Specifically, I will discuss some recent advances including how we can obtain a near-optimal solution to the DSP without maximum flows, motif-aware extensions of the DSP that enable the discovery of large-near cliques in massive networks, and risk-averse versions of the DSP on graphs whose edges are naturally associated with uncertainty.

Speaker Bio

Charalampos Tsourakakis is an Assistant Professor in Computer Science at Boston University. He obtained his PhD in the Algorithms, Combinatorics and Optimization program at Carnegie Mellon under the supervision of Alan Frieze, he was a postdoctoral fellow at Brown University and Harvard University mentored by Eli Upfal and Michael Mitzenmacher respectively. Before joining Boston University, he worked as a researcher in the Google Brain team. He won a best paper award in IEEE Data Mining, has delivered three tutorials in the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, and has designed two graph mining libraries for large-scale graph mining, one of which has been officially included in Windows Azure. His research focuses on large-scale graph mining, and machine learning.

eTALK Information

Topic: eTALK | Recent Advances in Dense Subgraph Discovery | Ass. Prof. Ch. Tsourakakis
Time: Feb 24, 2021 14:00 Athens

Join Zoom Meeting
https://us02web.zoom.us/j/82534638223?pwd=bHFyTnlUUDVUaHk5N1pWazdqWDZtdz09

Meeting ID: 825 3463 8223
Passcode: 309083

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