Speaker: Daniel Keren, Haifa University, Israel
Location: Warren Weaver Hall 1302
Date: October 1, 2010, 11:30 a.m.
Host: Zvi Kedem
Monitoring distributed data streams is the focus of much research in recent years, with applications in dynamic, distributed database systems and sensor networks. Most solutions, however, deal with monitoring simple aggregated values, such as the frequency of appearance of items in the streams. More involved challenges, such as dynamic feature selection, or generally monitoring non-linear functions, are yet to be solved. In this talk I will present a general approach to this problem, based on studying the geometric properties of the domain of the monitored functions.
Joint work with Assaf Schuster, Izchak Sharfman, and Guy Sagy, Technion.
Daniel Keren obtained his Ph.D degree from the Hebrew University in 1991. After doing post-doctoral work at Brown University, he joined the University of Haifa. He is interested mostly in computer vision, machine learning, and the analysis of large-scale dynamic data.
Refreshments will be offered starting 15 minutes prior to the scheduled start of the talk.