TY - GEN
T1 - Signal detection on graphs
T2 - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
AU - Chen, Siheng
AU - Yang, Yaoqing
AU - Singh, Aarti
AU - Kovačević, Jelena
N1 - Funding Information:
The authors gratefully acknowledge support from the NSF through awards 1130616 and 1017278, and CMU Carnegie Institute of Technology Infrastructure Award.
Publisher Copyright:
© 2016 IEEE.
PY - 2017/4/19
Y1 - 2017/4/19
N2 - We consider detecting localized binary attributes on a graph. A localized binary attribute means that the nodes activated by the attribute form form a subgraph that can be easily separated from the other nodes. We formulate a statistical hypothesis test to decide whether a given attribute is localized or not. We propose two statistics: graph wavelet statistic and graph scan statistic. Both are shown to be efficient and statistically effective. We further apply the proposed methods to rank research keywords as attributes in a coauthorship network collected from IEEE Xplore. The experimental results show that the proposed graph wavelet statistic and graph scan statistic are effective and efficient.1
AB - We consider detecting localized binary attributes on a graph. A localized binary attribute means that the nodes activated by the attribute form form a subgraph that can be easily separated from the other nodes. We formulate a statistical hypothesis test to decide whether a given attribute is localized or not. We propose two statistics: graph wavelet statistic and graph scan statistic. Both are shown to be efficient and statistically effective. We further apply the proposed methods to rank research keywords as attributes in a coauthorship network collected from IEEE Xplore. The experimental results show that the proposed graph wavelet statistic and graph scan statistic are effective and efficient.1
UR - http://www.scopus.com/inward/record.url?scp=85019183692&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019183692&partnerID=8YFLogxK
U2 - 10.1109/GlobalSIP.2016.7905871
DO - 10.1109/GlobalSIP.2016.7905871
M3 - Conference contribution
AN - SCOPUS:85019183692
T3 - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
SP - 395
EP - 399
BT - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 December 2016 through 9 December 2016
ER -