Published in Proceedings of the ACM on Management of Data (SIGMOD 2026), 2026
Recommended citation: Mingyi Huang, Qinghua Liu, Paul Boniol, John Paparrizos. (2026). HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series. https://doi.org/10.1145/3788853.3801594
Published in SIGMOD Companion 2026, 2026
Recommended citation: Mingyi Huang, Qinghua Liu, Paul Boniol, John Paparrizos. (2026). GlassboxAD: An Interactive System for Dissecting Hierarchical Time-Series Anomaly Detection.
Published in The VLDB Journal, 2025
Recommended citation: Paul Boniol, Ashwin K. Krishna, Marine Bruel, Qinghua Liu, Mingyi Huang, Themis Palpanas, Ruey S. Tsay, Aaron Elmore, Michael J. Franklin, John Paparrizos. (2025). VUS: effective and efficient accuracy measures for time-series anomaly detection. https://link.springer.com/article/10.1007/s00778-025-00907-x
Published in arXiv preprint arXiv:2412.20512, 2024
Recommended citation: Paul Boniol, Qinghua Liu, Mingyi Huang, Themis Palpanas, John Paparrizos. (2024). Dive into Time-Series Anomaly Detection: A Decade Review. https://arxiv.org/abs/2412.20512
Published in NeurIPS 2023 spotlight, 2023
Recommended citation: Liyuan Wang, Jingyi Xie, Xingxing Zhang, Mingyi Huang, Hang Su, Jun Zhu. (2023). Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality https://arxiv.org/abs/2310.07234