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Capturing Evolution Genes for Time Series Data. (arXiv:1905.05004v2 [cs.LG] UPDATED)
July 13, 2022, 1:11 a.m. | Wenjie Hu, Jianping Huang, Liang Wu, Yang Yang, Zongtao Liu, Zhanlin Sun, Bingshen Yao, Ke Chen
stat.ML updates on arXiv.org arxiv.org
The modeling of time series is becoming increasingly critical in a wide
variety of applications. Overall, data evolves by following different patterns,
which are generally caused by different user behaviors. Given a time series, we
define the evolution gene to capture the latent user behaviors and to describe
how the behaviors lead to the generation of time series. In particular, we
propose a uniform framework that recognizes different evolution genes of
segments by learning a classifier, and adopt an adversarial …
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