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- W4308216144 abstract "We propose an online detection procedure for cascading failures in the network from sequential data, which can be modeled as multiple correlated change-points happening during a short period. We consider a temporal diffusion network model to capture the temporal dynamic structure of multiple change-points and develop a sequential Shewhart procedure based on the generalized likelihood ratio statistics based on the diffusion network model assuming unknown post-change distribution parameters. We also tackle the computational complexity posed by the unknown propagation. Numerical experiments demonstrate good performance for detecting cascade failures." @default.
- W4308216144 created "2022-11-09" @default.
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- W4308216144 date "2022-09-27" @default.
- W4308216144 modified "2023-10-16" @default.
- W4308216144 title "Online Detection of Cascading Change-Points Using Diffusion Networks" @default.
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- W4308216144 doi "https://doi.org/10.1109/allerton49937.2022.9929381" @default.
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