149 citations · 358 across the 15 of their papers we have counts for
18 papers
Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series
Audrey Der, Chin-Chia Michael Yeh, Renjie Wu +6
The most useful data mining primitives are distance measures. With an effective distance measure, it is possible to perform classification, clustering, anomaly detection, segmentat…
Error-bounded Approximate Time Series Joins Using Compact Dictionary Representations of Time Series
Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang +4
The matrix profile is an effective data mining tool that provides similarity join functionality for time series data. Users of the matrix profile can either join a time series with…
When is Early Classification of Time Series Meaningful?
Renjie Wu, Audrey Der, Eamonn J. Keogh
Since its introduction two decades ago, there has been increasing interest in the problem of early classification of time series. This problem generalizes classic time series class…
Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW
Sara Alaee, Kaveh Kamgar, Eamonn Keogh
Over the last decade, time series motif discovery has emerged as a useful primitive for many downstream analytical tasks, including clustering, classification, rule discovery, segm…
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress
Renjie Wu, Eamonn J. Keogh
Time series anomaly detection has been a perennially important topic in data science, with papers dating back to the 1950s. However, in recent years there has been an explosion of…
Matrix Profile Goes MAD: Variable-Length Motif And Discord Discovery in Data Series
Michele Linardi, Yan Zhu, Themis Palpanas +1
In the last fifteen years, data series motif and discord discovery have emerged as two useful and well-used primitives for data series mining, with applications to many domains, in…