Web: http://arxiv.org/abs/2201.11678

Jan. 28, 2022, 2:11 a.m. | Sudarshan Adiga, Ravi Tandon

cs.LG updates on arXiv.org arxiv.org

This paper presents DRE-CUSUM, an unsupervised density-ratio estimation (DRE)
based approach to determine statistical changes in time-series data when no
knowledge of the pre-and post-change distributions are available. The core idea
behind the proposed approach is to split the time-series at an arbitrary point
and estimate the ratio of densities of distribution (using a parametric model
such as a neural network) before and after the split point. The DRE-CUSUM
change detection statistic is then derived from the cumulative sum (CUSUM) …

arxiv change detection unsupervised

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