Parameter Transfer
Parameter Transfer is a transfer learning strategy that involves the direct reuse of learned model parameters from a source task to a target task, distinguishing itself by leveraging pre-trained weights to initialize or guide the learning process in a new but related domain.
112
Publications
6.6K
Citations
410
Authors
180
Institutions
Publications per year
2017–2026
96
Parents
112
Predicting the Discharge of Global Rivers
Bart Nijssen, Greg O’Donnell, Dennis P. Lettenmaier et al. · Journal of Climate · 2001 · 569 citations
Min Xia, Guangjie Han, Yu Zhang et al. · IEEE Transactions on Industrial Informatics · 2020 · 439 citations · Full text
Deep Reinforcement Learning for Multiobjective Optimization
Kaiwen Li, Tao Zhang, Rui Wang · IEEE Transactions on Cybernetics · 2020 · 400 citations · Full text
Towards a Unified View of Parameter-Efficient Transfer Learning
Junxian He, Chunting Zhou, Xuezhe Ma et al. · arXiv (Cornell University) · 2021 · 280 citations · Full text
Yu-Xiong Wang, Deva Ramanan, Martial Hebert · Neural Information Processing Systems · 2017 · 267 citations
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180
Queen Mary University of London
London, United Kingdom
6 h-index
11 publications
356 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
15 publications
1.2K citations
Google (United States)
Mountain View, United States
4 h-index
10 publications
740 citations

Shanghai University
Shanghai, China
4 h-index
19 publications
798 citations
Amazon (United States)
Seattle, United States
4 h-index
10 publications
479 citations

Northwestern Polytechnical University
Xi'an, China
3 h-index
9 publications
506 citations

Hunan University
Changsha, China
3 h-index
8 publications
1.3K citations

Huazhong University of Science and Technology
Wuhan, China
3 h-index
12 publications
364 citations
1–8 of 180
Repository · 16 publications · 954 citations
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4 publications · 174 citations
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4 publications · 164 citations
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3 publications · 212 citations
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2 publications · 28 citations
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