HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series

Authors

• 1. Mingyi Huang (Ohio State University)
• 2. Qinghua Liu (Ohio State University)
• 3. Paul Boniol (CNRS; INRIA; Paris Sciences et Lettres University; École Normale Supérieure)
• 4. John Paparrizos (Aristotle University of Thessaloniki; Ohio State University)

@inproceedings{huang_sigmod26,
        title = {{HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series}},
        author = {Huang, Mingyi and Liu, Qinghua and Boniol, Paul and Paparrizos, John},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3802074},
        url = {https://dl.acm.org/doi/10.1145/3802074},
        year = {2026}
}

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