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Renjie Wu
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Year
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress
R Wu, E Keogh
IEEE Transactions on Knowledge and Data Engineering 35 (3), 2421-2429, 2021
1792021
FastDTW is approximate and Generally Slower than the Algorithm it Approximates
R Wu, EJ Keogh
IEEE Transactions on Knowledge and Data Engineering 34 (8), 3779-3785, 2020
422020
Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams
Y Lu, R Wu, A Mueen, MA Zuluaga, E Keogh
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
302022
When is Early Classification of Time Series Meaningful?
R Wu, A Der, E Keogh
IEEE Transactions on Knowledge and Data Engineering 35 (3), 3253-3260, 2021
142021
DAMP: Accurate Time Series Anomaly Detection on Trillions of Datapoints and Ultra-fast Arriving Data Streams
Y Lu, R Wu, A Mueen, MA Zuluaga, E Keogh
Data Mining and Knowledge Discovery 37 (2), 627-669, 2023
62023
Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series
A Der, CCM Yeh, R Wu, J Wang, Y Zheng, Z Zhuang, L Wang, W Zhang, ...
2022 IEEE International Conference on Knowledge Graph (ICKG), 40-47, 2022
12022
Matrix Profile XXIX: C22MP, Fusing catch 22 and the Matrix Profile to Produce an Efficient and Interpretable Anomaly Detector
S Tafazoli, Y Lu, R Wu, TVA Srinivas, HD Cruz, R Mercer, E Keogh
2023 IEEE International Conference on Data Mining (ICDM), 568-577, 2023
2023
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