TY - GEN
T1 - Dynamic Search on a Tree with Information-Directed Random Walk
AU - Wang, Chao
AU - Zhao, Qing
AU - Cohen, Kobi
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/24
Y1 - 2018/8/24
N2 - The problem of detecting a few anomalous processes among a large number of data streams is considered. At each time, aggregated observations can be taken from a chosen subset of the processes, where the chosen subset conforms to a given tree structure. The random observations are drawn from a general distribution that may depend on the size of the chosen subset and the number of anomalous processes in the subset. We propose a sequential search strategy by devising an information-directed random walk (IRW) on the tree-structured observation hierarchy. The sample complexity of the IRW policy is shown to be asymptotically optimal with respect to the detection accuracy and order optimal with respect to the number of data streams. The results also find applications in noisy group testing, active learning, and channel coding with feedback.
AB - The problem of detecting a few anomalous processes among a large number of data streams is considered. At each time, aggregated observations can be taken from a chosen subset of the processes, where the chosen subset conforms to a given tree structure. The random observations are drawn from a general distribution that may depend on the size of the chosen subset and the number of anomalous processes in the subset. We propose a sequential search strategy by devising an information-directed random walk (IRW) on the tree-structured observation hierarchy. The sample complexity of the IRW policy is shown to be asymptotically optimal with respect to the detection accuracy and order optimal with respect to the number of data streams. The results also find applications in noisy group testing, active learning, and channel coding with feedback.
KW - Sequential design of experiments
KW - active hypothesis testing
KW - anomaly detection
KW - channel coding with feedback
KW - noisy group testing
UR - http://www.scopus.com/inward/record.url?scp=85053449476&partnerID=8YFLogxK
U2 - 10.1109/SPAWC.2018.8445913
DO - 10.1109/SPAWC.2018.8445913
M3 - Conference contribution
AN - SCOPUS:85053449476
SN - 9781538635124
T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
BT - 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
PB - Institute of Electrical and Electronics Engineers
T2 - 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
Y2 - 25 June 2018 through 28 June 2018
ER -