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TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection., , , , , and . Proc. VLDB Endow., 15 (8): 1697-1711 (2022)AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments., , , , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 7 (1): 21:1-21:26 (March 2023)k-Shape: Efficient and Accurate Clustering of Time Series., and . SIGMOD Rec., 45 (1): 69-76 (2016)Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection., , , , , , and . Proc. VLDB Endow., 15 (12): 3702-3705 (2022)Odyssey: An Engine Enabling The Time-Series Clustering Journey., and . Proc. VLDB Endow., 16 (12): 4066-4069 (2023)Fast and Accurate Time-Series Clustering., and . ACM Trans. Database Syst., 42 (2): 8:1-8:49 (2017)Detecting Devastating Diseases in Search Logs., , and . KDD, page 559-568. ACM, (2016)k-Shape: Efficient and Accurate Clustering of Time Series., and . SIGMOD Conference, page 1855-1870. ACM, (2015)Band-limited Training and Inference for Convolutional Neural Networks., , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 1745-1754. PMLR, (2019)Predicting the impact of scientific concepts using full-text features, , , , , , , , , and 10 other author(s). Journal of the Association for Information Science and Technology, (2016)