Self-supervised autoregressive domain adaptation for time series data

• Main Authors: Ragab, Mohamed, Eldele, Emadeldeen, Chen, Zhenghua, Wu, Min, Kwoh, Chee Keong, Li, Xiaoli
• 其他作者: School of Computer Science and Engineering
• 格式: Article
• 語言: English
• 出版: 2023
• 主題: Engineering::Computer science and engineering; Autoregressive Domain Adaptation; Ensemble Teacher Learning
• 在線閱讀: https://hdl.handle.net/10356/164530

Unsupervised domain adaptation (UDA) has successfully addressed the domain shift problem for visual applications. Yet, these approaches may have limited performance for time series data due to the following reasons. First, they mainly rely on the large-scale dataset (i.e., ImageNet) for source pretr...