Deep Canonical Time Warping for Simultaneous Alignment and Representation Learning of Sequences

Machine learning algorithms for the analysis of time-series often depend on the assumption that utilised data are temporally aligned. Any temporal discrepancies arising in the data is certain to lead to ill-generalisable models, which in turn fail to correctly capture properties of the task at hand....

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Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 40(2018), 5 vom: 14. Mai, Seite 1128-1138
1. Verfasser:	Trigeorgis, George (VerfasserIn)
Weitere Verfasser:	Nicolaou, Mihalis A, Schuller, Bjorn W, Zafeiriou, Stefanos
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2018
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article Research Support, Non-U.S. Gov't