Effectively detecting and diagnosing distributed multivariate time series anomalies via Unsupervised Federated Hypernetwork.
Junfeng Hao|Peng Chen|Juan Chen|Xi Li
| Anthology ID: | DBLP:journals/ipm/HaoCCL25 |
|---|---|
| Year: | 2025 |
| Venue: | Information Processing and Management |
| Pages: | 104107 |
| URL: | https://doi.org/10.1016/J.IPM.2025.104107 |
| DOI: | https://doi.org/10.1016/J.IPM.2025.104107 |
| DBLP: | journals/ipm/HaoCCL25 |
| BibTeX: |
@article{hao-2025-effectively,
author = {Junfeng Hao and
Peng Chen and
Juan Chen and
Xi Li},
title = {{Effectively detecting and diagnosing distributed multivariate time series anomalies via Unsupervised Federated Hypernetwork}},
journal = {Information Processing and Management},
volume = {62},
number = {4},
pages = {104107},
year = {2025},
url = {https://doi.org/10.1016/J.IPM.2025.104107},
doi = {https://doi.org/10.1016/J.IPM.2025.104107}
}