Faster Domain Adaptation Networks

It is widely acknowledged that the success of deep learning is built upon large-scale training data and tremendous computing power. However, the data and computing power are not always available for many real-world applications. In this paper, we address the machine learning problem where it lacks t...

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Bibliographic Details
Published in:IEEE transactions on knowledge and data engineering 2022-12, Vol.34 (12), p.5770-5783
Main Authors: Li, Jingjing, Jing, Mengmeng, Su, Hongzu, Lu, Ke, Zhu, Lei, Shen, Heng Tao
Format: Article
Language:English
Subjects:
Acceleration
Adaptation
Adaptation models
Computational modeling
Deep learning
Domain adaptation
Domains
Edge computing
Knowledge management
Machine learning
model acceleration
Neural networks
Protocols
Task analysis
Training
transfer learning
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