activity
20182022
most citedMatrix Profile Goes MAD: Variable-Length Motif And Discord Discovery in Data Series

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.DB20202 cited

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…

cs.DB2020

VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series

Michele Linardi, Yan Zhu, Themis Palpanas +1

Data series motif discovery represents one of the most useful primitives for data series mining, with applications to many domains, such as robotics, entomology, seismology, medici…

cs.LG2018

Representation Learning by Reconstructing Neighborhoods

Chin-Chia Michael Yeh, Yan Zhu, Evangelos E. Papalexakis +2

Since its introduction, unsupervised representation learning has attracted a lot of attention from the research community, as it is demonstrated to be highly effective and easy-to-…

cs.LG2018

The UCR Time Series Archive

Hoang Anh Dau, Anthony Bagnall, Kaveh Kamgar +5

The UCR Time Series Archive - introduced in 2002, has become an important resource in the time series data mining community, with at least one thousand published papers making use…

cs.LG2018

Admissible Time Series Motif Discovery with Missing Data

Yan Zhu, Abdullah Mueen, Eamonn Keogh

The discovery of time series motifs has emerged as one of the most useful primitives in time series data mining. Researchers have shown its utility for exploratory data mining, sum…