EE Seminar: Dr. Kobi Cohen
~~ (The talk will be given in English)
Speaker: Dr. Kobi Cohen
Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign.
Wednesday, January 28th, 2015
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering
Active Learning for Dynamic Search Problems in Large-Scale Systems
Abstract
As networks are expected to grow more complex, developing effective algorithms for information gathering becomes more critical for learning tasks. In active learning (first considered by Chernoff in 1959, referred to as sequential design of experiments), a decision maker is required to actively choose among different processes to effectively shape the quality of the observations so as to optimize certain objectives in the system. In this talk I will present several results from my research on active learning for dynamic search problems (referred to as anomaly detection). We consider a system with a large number of processes, among which a few are anomalous. At each time, a subset of the processes can be observed, and the observations from each chosen process follow two different distributions, depending on whether the process is normal or abnormal. The problem is to find a sequential search strategy that optimizes a certain objective in the network (e.g., detection delay, cost) subject to reliability constraints. (Asymptotically) optimal algorithms will be presented to solve the anomaly detection problem under different objectives. The problems considered in this work find applications in anomaly detection in cyber systems, spectrum scanning in cognitive-radio networks, target search, and event detection in sensor networks.
Bio:
Kobi Cohen received the B.Sc. (cum laude) and Ph.D. degrees in electrical engineering from Bar-Ilan University, Ramat Gan, Israel, in 2007 and 2013, respectively. He is currently a postdoctoral research associate at the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. Before joining UIUC, he was with the Department of Electrical and Computer Engineering at the University of California, Davis, as a postdoctoral researcher. His main research interests include decision theory, stochastic optimization, multi-agent learning, game theory and statistical inference, with applications in dynamic systems, cyber-security, wireless and wireline networks.
