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ORCIDRenjie Wu 0001
Person information
- affiliation: University of California, Riverside, CA, USA
Other persons with the same name
- Renjie Wu 0002 — Waseda University, Japan
- Renjie Wu 0003
![[0000-0002-7356-8137]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-7356-8137")
— University of Nottingham Ningbo, School of Computer Science, China - Renjie Wu 0004 — ZheJiang Dahua Technology Co., Ltd, Hangzhou, China
- Renjie Wu 0005 — Shanghai University, Shanghai, China
- Renjie Wu 0006 — Guizhou University of Finance and Economics, Guiyang, China
- Renjie Wu 0007 — Hebei North University, Zhangjiakou, China
- Renjie Wu 0008 — University of Adelaide, Australia
- Renjie Wu 0009 — Peking University, College of Future Technology, Department of Big Data and Biomedical AI, Beijing, China
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2020 – today
- 2024
[b1]Renjie Wu:
Problems with Problems in Data Mining. University of California, Riverside, USA, 2024- [j5]Sadaf Tafazoli, Yue Lu, Renjie Wu, Thirumalai Vinjamoor Akhil Srinivas, Hannah Dela Cruz, Ryan Mercer, Eamonn J. Keogh:
C22MP: the marriage of catch22 and the matrix profile creates a fast, efficient and interpretable anomaly detector. Knowl. Inf. Syst. 66(8): 4789-4823 (2024) - 2023
- [j4]Yue Lu, Renjie Wu, Abdullah Mueen, Maria A. Zuluaga, Eamonn J. Keogh:
DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams. Data Min. Knowl. Discov. 37(2): 627-669 (2023) - [j3]Renjie Wu, Eamonn J. Keogh:
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress. IEEE Trans. Knowl. Data Eng. 35(3): 2421-2429 (2023) - [j2]Renjie Wu, Audrey Der, Eamonn J. Keogh:
When is Early Classification of Time Series Meaningful? IEEE Trans. Knowl. Data Eng. 35(3): 3253-3260 (2023) - [c6]Sadaf Tafazoli, Yue Lu, Renjie Wu, Thirumalai Vinjamoor Akhil Srinivas, Hannah Dela Cruz, Ryan Mercer, Eamonn J. Keogh:
Matrix Profile XXIX: C22MP, Fusing catch 22 and the Matrix Profile to Produce an Efficient and Interpretable Anomaly Detector. ICDM 2023: 568-577 - 2022
- [j1]Renjie Wu, Eamonn J. Keogh:
FastDTW is Approximate and Generally Slower Than the Algorithm it Approximates. IEEE Trans. Knowl. Data Eng. 34(8): 3779-3785 (2022) - [c5]Audrey Der, Chin-Chia Michael Yeh, Renjie Wu, Junpeng Wang, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh:
Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series. ICKG 2022: 40-47 - [c4]Renjie Wu, Audrey Der, Eamonn J. Keogh:
When is Early Classification of Time Series Meaningful? (Extended Abstract). ICDE 2022: 1477-1478 - [c3]Renjie Wu, Eamonn J. Keogh:
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress (Extended Abstract). ICDE 2022: 1479-1480 - [c2]Yue Lu, Renjie Wu, Abdullah Mueen, Maria A. Zuluaga, Eamonn J. Keogh:
Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams. KDD 2022: 1173-1182 - [i4]Audrey Der, Chin-Chia Michael Yeh, Renjie Wu, Junpeng Wang, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh:
Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series. CoRR abs/2212.06146 (2022) - 2021
- [c1]Renjie Wu, Eamonn J. Keogh:
FastDTW is approximate and Generally Slower than the Algorithm it Approximates (Extended Abstract). ICDE 2021: 2327-2328 - [i3]Renjie Wu, Audrey Der, Eamonn J. Keogh:
When is Early Classification of Time Series Meaningful? CoRR abs/2102.11487 (2021) - 2020
- [i2]Renjie Wu, Eamonn J. Keogh:
FastDTW is approximate and Generally Slower than the Algorithm it Approximates. CoRR abs/2003.11246 (2020) - [i1]Renjie Wu, Eamonn J. Keogh:
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress. CoRR abs/2009.13807 (2020)
Coauthor Index
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