Artículos con órdenes de acceso público - Eamonn KeoghMás información
No disponibles en ningún lugar: 6
Reliable early classification of time series based on discriminating the classes over time
U Mori, A Mendiburu, E Keogh, JA Lozano
Data mining and knowledge discovery 31, 233-263, 2017
Órdenes: Gobierno de España
Time series motifs discovery under DTW allows more robust discovery of conserved structure
S Alaee, R Mercer, K Kamgar, E Keogh
Data Mining and Knowledge Discovery 35, 863-910, 2021
Órdenes: US National Science Foundation
Classification of streaming time series under more realistic assumptions
B Hu, Y Chen, E Keogh
Data mining and knowledge discovery 30 (2), 403-437, 2016
Órdenes: US National Science Foundation
Introducing time series snippets: a new primitive for summarizing long time series
S Imani, F Madrid, W Ding, SE Crouter, E Keogh
Data Mining and Knowledge Discovery 34, 1713-1743, 2020
Órdenes: US National Science Foundation, US National Institutes of Health
Matrix profile xxv: introducing novelets: a primitive that allows online detection of emerging behaviors in time series
R Mercer, E Keogh
2022 IEEE international conference on data mining (ICDM), 338-347, 2022
Órdenes: US National Science Foundation
Getting an h-Index of 100 in 20 Years or Less!
E Keogh
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
Órdenes: US National Science Foundation
Disponibles en algún lugar: 50
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
A Bagnall, J Lines, A Bostrom, J Large, E Keogh
Data mining and knowledge discovery 31, 606-660, 2017
Órdenes: UK Engineering and Physical Sciences Research Council
Searching and mining trillions of time series subsequences under dynamic time warping
T Rakthanmanon, B Campana, A Mueen, G Batista, B Westover, Q Zhu, ...
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
Órdenes: US National Institutes of Health
Exact discovery of time series motifs
A Mueen, E Keogh, Q Zhu, S Cash, B Westover
Proceedings of the 2009 SIAM international conference on data mining, 473-484, 2009
Órdenes: US National Institutes of Health
Addressing big data time series: Mining trillions of time series subsequences under dynamic time warping
T Rakthanmanon, B Campana, A Mueen, G Batista, B Westover, Q Zhu, ...
ACM Transactions on Knowledge Discovery from Data (TKDD) 7 (3), 1-31, 2013
Órdenes: US National Institutes of Health
Generalizing DTW to the multi-dimensional case requires an adaptive approach
M Shokoohi-Yekta, B Hu, H Jin, J Wang, E Keogh
Data mining and knowledge discovery 31, 1-31, 2017
Órdenes: US National Science Foundation, Bill & Melinda Gates Foundation, US National …
Matrix profile ii: Exploiting a novel algorithm and gpus to break the one hundred million barrier for time series motifs and joins
Y Zhu, Z Zimmerman, NS Senobari, CCM Yeh, G Funning, A Mueen, ...
2016 IEEE 16th international conference on data mining (ICDM), 739-748, 2016
Órdenes: US National Science Foundation
Extracting optimal performance from dynamic time warping
A Mueen, E Keogh
Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016
Órdenes: US National Science Foundation
Generating synthetic time series to augment sparse datasets
G Forestier, F Petitjean, HA Dau, GI Webb, E Keogh
2017 IEEE international conference on data mining (ICDM), 865-870, 2017
Órdenes: US Department of Defense, Australian Research Council
Matrix profile VI: Meaningful multidimensional motif discovery
CCM Yeh, N Kavantzas, E Keogh
2017 IEEE international conference on data mining (ICDM), 565-574, 2017
Órdenes: US National Science Foundation
On the non-trivial generalization of dynamic time warping to the multi-dimensional case
M Shokoohi-Yekta, J Wang, E Keogh
Proceedings of the 2015 SIAM international conference on data mining, 289-297, 2015
Órdenes: US National Institutes of Health
Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile
CCM Yeh, Y Zhu, L Ulanova, N Begum, Y Ding, HA Dau, Z Zimmerman, ...
Data Mining and Knowledge Discovery 32, 83-123, 2018
Órdenes: US National Science Foundation
Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm
F Petitjean, G Forestier, GI Webb, AE Nicholson, Y Chen, E Keogh
Knowledge and Information Systems 47, 1-26, 2016
Órdenes: US National Science Foundation, Bill & Melinda Gates Foundation, Australian …
Matrix profile VIII: domain agnostic online semantic segmentation at superhuman performance levels
S Gharghabi, Y Ding, CCM Yeh, K Kamgar, L Ulanova, E Keogh
2017 IEEE international conference on data mining (ICDM), 117-126, 2017
Órdenes: US National Science Foundation
Matrix profile vii: Time series chains: A new primitive for time series data mining (best student paper award)
Y Zhu, M Imamura, D Nikovski, E Keogh
2017 IEEE international conference on data mining (ICDM), 695-704, 2017
Órdenes: US National Science Foundation
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