Learning Transferable Features with Deep Adaptation Networks
Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually...
Publications
4 shownAutoformer: Decomposition Transformers with Auto-Correlation for\n Long-Term Series Forecasting
Extending the forecasting time is a critical demand for real applications,\nsuch as extreme weather early warning and long-term energy consumption\nplanning. This paper studies ...
Transfer Feature Learning with Joint Distribution Adaptation
Transfer learning is established as an effective technology in computer vision for leveraging rich labeled data in the source domain to build an accurate classifier for the targ...
Adaptation Regularization: A General Framework for Transfer Learning
Domain transfer learning, which learns a target classifier using labeled data from a different distribution, has shown promising value in knowledge discovery yet still been a ch...
Frequent Co-Authors
Researcher Info
- h-index
- 4
- Publications
- 4
- Citations
- 5,138
- Institution
- Tsinghua University
External Links
Identifiers
- ORCID
- 0000-0001-9421-463X
Impact Metrics
h-index
4
h-index: Number of publications with at least h citations each.