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Large volumes of networked streaming event data are becoming increasingly available in a wide variety of applications such as social network analysis, Internet traffic monitoring, and health care analytics. Streaming event data are discrete observations occurring in continuous time, and the precise time interval between two events carries substantial information about the dynamics of the underlying...
We study sequential change-point detection using sketches (or linear projections) of the high-dimensional data vectors, and present a new sketching procedure, which is based on the generalized likelihood ratio statistic. We derive theoretical approximations to two fundamental performance metrics for the sketching procedures: the average run length (ARL) and the expected detection delay (EDD), and...
This paper describes a new algorithm for recovering low-rank matrices from their linear measurements contaminated with Poisson noise: the Poisson noise Maximum Likelihood Singular Value thresholding (PMLSV) algorithm. We propose a convex optimization formulation with a cost function consisting of the sum of a likelihood function and a regularization function which is proportional to the nuclear norm...
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