Self-supervised autoregressive domain adaptation for time series data

Self-supervised autoregressive domain adaptation for time series data

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...

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書目詳細資料
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
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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