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Helga Van Herle
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2010 – 2019
- 2016
- [c4]Chin-Chia Michael Yeh, Helga Van Herle, Eamonn J. Keogh:
Matrix Profile III: The Matrix Profile Allows Visualization of Salient Subsequences in Massive Time Series. ICDM 2016: 579-588
2000 – 2009
- 2009
- [j4]Suleyman Serdar Kozat, Michail Vlachos
, Claudio Lucchese
, Helga Van Herle, Philip S. Yu:
Embedding and Retrieving Private Metadata in Electrocardiograms. J. Medical Syst. 33(4): 241-259 (2009) - 2007
- [j3]Eamonn J. Keogh, Jessica Lin, Sang-Hee Lee, Helga Van Herle:
Finding the most unusual time series subsequence: algorithms and applications. Knowl. Inf. Syst. 11(1): 1-27 (2007) - [j2]Li Wei, Eamonn J. Keogh, Helga Van Herle, Agenor Mafra-Neto, Russell J. Abbott:
Efficient query filtering for streaming time series with applications to semisupervised learning of time series classifiers. Knowl. Inf. Syst. 11(3): 313-344 (2007) - 2006
- [j1]Eamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu, Helga Van Herle:
Finding Unusual Medical Time-Series Subsequences: Algorithms and Applications. IEEE Trans. Inf. Technol. Biomed. 10(3): 429-439 (2006) - 2005
- [c3]Jessica Lin, Eamonn J. Keogh, Ada Wai-Chee Fu, Helga Van Herle:
Approximations to Magic: Finding Unusual Medical Time Series. CBMS 2005: 329-334 - [c2]Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamonn J. Keogh, Stefano Lonardi
, Chotirat (Ann) Ratanamahatana, Helga Van Herle:
A Practical Tool for Visualizing and Data Mining Medical Time Series. CBMS 2005: 341-346 - [c1]Li Wei, Eamonn J. Keogh, Helga Van Herle, Agenor Mafra-Neto:
Atomic Wedgie: Efficient Query Filtering for Streaming Times Series. ICDM 2005: 490-497
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