583 citations to https://www.mathnet.ru/rus/tvp4645
  1. Taposh Banerjee, Miao Liu, Jonathan P. How, 2017 American Control Conference (ACC), 2017, 399  crossref
  2. Jasmin James, Jason J. Ford, Timothy L. Molloy, 2017 11th Asian Control Conference (ASCC), 2017, 2066  crossref
  3. Polunchenko A.S. Sokolov G., “An Analytic Expression for the Distribution of the Generalized Shiryaev–Roberts Diffusion”, Methodol. Comput. Appl. Probab., 18:4, SI (2016), 1153–1195  crossref  mathscinet  isi  elib  scopus
  4. Molloy T.L. Ford J.J., “Asymptotic Minimax Robust Quickest Change Detection for Dependent Stochastic Processes With Parametric Uncertainty”, IEEE Trans. Inf. Theory, 62:11 (2016), 6594–6608  crossref  mathscinet  zmath  isi  scopus
  5. Dayanik S. Sezer S.O., “Sequential Sensor Installation for Wiener Disorder Detection”, Math. Oper. Res., 41:3 (2016), 827–850  crossref  mathscinet  zmath  isi  elib  scopus
  6. Ye S., Fellouris G., Culpepper S., Douglas J., “Sequential detection of learning in cognitive diagnosis”, Br. J. Math. Stat. Psychol., 69:2 (2016), 139–158  crossref  mathscinet  isi  scopus
  7. Polunchenko A.S., “Exact distribution of the Generalized Shiryaev–Roberts stopping time under the minimax Brownian motion setup”, Seq. Anal., 35:1, SI (2016), 108–143  crossref  mathscinet  zmath  isi  elib  scopus
  8. Li D., Kar S., Cui Sh., “Distributed Bayesian Quickest Change Detection in Sensor Networks Via Large Deviation Analysis”, 2016 54Th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Annual Allerton Conference on Communication Control and Computing, IEEE, 2016, 1274–1281  isi
  9. Chronopoulou A., Nagi R., “Online Community Detection For Fused Social Network Graphs”, 2016 19Th International Conference on Information Fusion (Fusion), IEEE, 2016, 1682–1686  isi
  10. Chen J. Zhang W. Poor H.V., “Non-Bayesian Multiple Change-Point Detection Controlling False Discovery Rate”, 2016 IEEE International Symposium on Information Theory, IEEE International Symposium on Information Theory, IEEE, 2016, 31–35  isi
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