*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
TITLE: Monitoring a Large Number of Data Streams via Thresholding
SPEAKER: Yajun Mei
ABSTRACT:
In the modern information age one often monitors a large number of data streams with the aim of offering the potential for early detection of a "trigger" event. In this talk, we are interested in detecting the event as soon as possible, but we do not know when the event will occur, nor do we know which subset of data streams will be affected by the event. Motivated by the applications in censoring sensor networks and by the case when one has a prior knowledge that at most r data streams will be affected, we propose scalable global monitoring schemes based on the sum of the local detection statistics that are "large" under either hard thresholding or top-r thresholding rules or both. The proposed schemes are shown to possess certain asymptotic optimality properties.
