Time-series representation learning via temporal and contextual contrasting

Time-series representation learning via temporal and contextual contrasting

Learning decent representations from unlabeled time-series data with temporal dynamics is a very challenging task. In this paper, we propose an unsupervised Time-Series representation learning framework via Temporal and Contextual Contrasting (TS-TCC), to learn time-series representation from unlabe...

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Bibliographic Details
Main Authors: Eldele, Emadeldeen, Mohamed Ragab, Chen, Zhenghua, Wu, Min, Kwoh, Chee Keong, Li, Xiaoli, Guan, Cuntai
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2022
Subjects:
Engineering::Computer science and engineering
Deep Learning
Semi-Supervised Learning
Time-Series
Machine Learning
Online Access:https://hdl.handle.net/10356/155626

Internet

https://hdl.handle.net/10356/155626

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