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TapNet: Multivariate Time Series Classification with Attentional Prototypical Network.

, , , and . AAAI, page 6845-6852. AAAI Press, (2020)

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Efficient Discovery of Variable-length Time Series Motifs with Large Length Range in Million Scale Time Series., and . CoRR, (2018)A Uniform Representation for Trajectory Learning Tasks., , , and . SIGSPATIAL/GIS, page 80:1-80:4. ACM, (2017)Finding Motifs in Time Series, , , and . ICDM, (2002)A Robot System for Pruning Grape Vines., , , , , , , , and . J. Field Robotics, 34 (6): 1100-1122 (2017)Frequent Set Mining for Streaming Mixed and Large Data., , and . ICMLA, page 1130-1135. IEEE, (2015)A Machine Learning Approach to False Alarm Detection for Critical Arrhythmia Alarms., , , , and . ICMLA, page 202-207. IEEE, (2015)PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time Series., , , and . SDM, page 891-899. SIAM, (2023)Semantic Discord: Finding Unusual Local Patterns for Time Series., , and . SDM, page 136-144. SIAM, (2020)The conference was canceled because of the coronavirus pandemic, the reviewed papers are published in this volume..Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research., , and . ICDM, page 115-122. IEEE Computer Society, (2003)Approximations to Magic: Finding Unusual Medical Time Series., , , and . CBMS, page 329-334. IEEE Computer Society, (2005)