Optimal Resolution of Change-Point Detection with Empirically Observed Statistics

13 Mar 2020 Haiyun He Qiaosheng Zhang Vincent Y. F. Tan

This paper revisits the offline change-point detection problem from a statistical learning perspective. Instead of assuming that the underlying pre- and post-change distributions are known, it is assumed that we have partial knowledge of these distributions based on empirically observed statistics in the form of training sequences... (read more)

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