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Eamonn J. Keogh

University of California - Riverside

10 papers hereh-index 9547.1k citations350 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author9

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.LG8
  • cs.DB2
affiliations
  • University of California - Riverside
Homepage
same name
  • Eamonn J. Keogh — 6 papers, h 8
  • Eamonn J. Keogh — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182020
most citedTime series classification for varying length series

19 citations · 22 across the 4 of their papers we have counts for

collaborators
Showing 2020Show all

3 papers · 1 filter

cs.LG2020

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…

cs.DB2020★ 2 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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.