•   When: Friday, March 25, 2016 from 11:00 AM to 12:00 PM
•   Speakers: Christos Faloutsos Professor, Department of Computer Science, Carnegie Mellon University
•   Location: Research Hall, Room 163
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Abstract

Given a large graph, like who-calls-whom, or who-likes-whom, what behavior is normal and what should be surprising, possibly due to fraudulent activity? How do graphs evolve over time?

We focus on these topics: (a) anomaly detection in large static graphs and (b) patterns and anomalies in large time-evolving graphs.

For the first, we present a list of static and temporal laws, including advances patterns like 'eigenspokes'; we show how to use them to spot suspicious activities, in on-line buyer-and-seller settings, in FaceBook, in twitter-like networks.

For the second, we show how to handle time-evolving graphs as tensors, as well as some discoveries such settings.

Bio

Professor, Department of Computer Science, Carnegie Mellon University Christos Faloutsos is a Professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by the National Science Foundation (1989), the Research Contributions Award in ICDM 2006, the SIGKDD Innovations Award (2010), 22 “best paper'' awards (including 4 “test of time'' awards), and four teaching awards. Six of his advisees have attracted KDD or SCS dissertation awards. He is an ACM Fellow, he has served as a member of the executive committee of SIGKDD; he has published over 350 refereed articles, 17 book chapters and two monographs. He holds seven patents (and 2 pending), and he has given over 40 tutorials and over 20 invited distinguished lectures. His research interests include large-scale data mining with emphasis on graphs and time sequences; anomaly detection, tensors, and fractals.