Self-supervised learning for time series analysis : Taxonomy, progress, and prospects

• Main Authors: ZHANG Kexin, WEN, Qingsong, ZHANG, Chaoli, CAI, Rongyao, JIN, Ming, LIU, Yong, ZHANG, James Y., PANG, Guansong, Guansong PANG, PAN Shirui
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Self-supervised learning; Time series data analysis; Time series taxonomy; Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/sis_research/9820; https://ink.library.smu.edu.sg/context/sis_research/article/10820/viewcontent/2306.10125v4.pdf
• Institution: Singapore Management University

Self-supervised learning (SSL) has recently achieved impressive performance on various time series tasks. The most prominent advantage of SSL is that it reduces the dependence on labeled data. Based on the pre-training and fine-tuning strategy, even a small amount of labeled data can achieve high pe...