1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Refining the Optimization Target for Automatic Univariate Time Series Anomaly Detection in Monitoring Services
Manqing Dong, Zhanxiang Zhao, Yitong Geng +3
Time series anomaly detection is crucial for industrial monitoring services that handle a large volume of data, aiming to ensure reliability and optimize system performance. Existi…
cs.LG2021★ 1 cited
Ymir: A Supervised Ensemble Framework for Multivariate Time Series Anomaly Detection
Zhanxiang Zhao
We proposed a multivariate time series anomaly detection frame-work Ymir, which leverages ensemble learning and supervisedlearning technology to efficiently learn and adapt to anom…