TY - GEN
T1 - Online parallel monitoring via hard-thresholding post-change estimation
AU - Wang, Yuan
AU - Mei, Yajun
PY - 2014
Y1 - 2014
N2 - The online parallel monitoring problem is studied when one is monitoring large-scale data streams, and an event occurs at an unknown time and affects an unknown subset of data streams. Efficient online parallel monitoring schemes are developed by combining the standard sequential change-point method with hard-thresholding post-change estimation. Theoretical analysis and simulation study demonstrate the usefulness of hard-thresholding for online parallel monitoring.
AB - The online parallel monitoring problem is studied when one is monitoring large-scale data streams, and an event occurs at an unknown time and affects an unknown subset of data streams. Efficient online parallel monitoring schemes are developed by combining the standard sequential change-point method with hard-thresholding post-change estimation. Theoretical analysis and simulation study demonstrate the usefulness of hard-thresholding for online parallel monitoring.
UR - http://www.scopus.com/inward/record.url?scp=84906534901&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84906534901&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2014.6875423
DO - 10.1109/ISIT.2014.6875423
M3 - Conference contribution
AN - SCOPUS:84906534901
SN - 9781479951864
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 3190
EP - 3194
BT - 2014 IEEE International Symposium on Information Theory, ISIT 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Symposium on Information Theory, ISIT 2014
Y2 - 29 June 2014 through 4 July 2014
ER -