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Abstract |
Monitoring high-dimensional data streams has become increasingly important for real-time detection of abnormal activities in many data-rich applications. In this talk, I will give a brief discussion on recent work from the following aspects: i) develop an efficient global monitoring procedure when we do not know which subset of data streams is affected by an occurring event; ii) suggest a procedure which is able to control the conditional false discovery rate at each time point when our focus is detecting changes in each individual data stream; iii) propose a distribution-free detection scheme in the sense that its in-control run-length distribution is free of the underlying distribution. |
