Adaptive Mutual Learning for Unsupervised Domain Adaptation
Author:
Affiliation:
1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
2. Surrey Institute for People-Centred Artificial Intelligence, CVSSP, University of Surrey, Guildford, U.K
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Sichuan Science and Technology Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Media Technology
Link
http://xplorestaging.ieee.org/ielx7/76/10297951/10097830.pdf?arnumber=10097830
Reference71 articles.
1. Domain Generalization for Object Recognition with Multi-task Autoencoders
2. Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
3. Unsupervised Domain Adaptation Using Robust Class-Wise Matching
4. Enhanced Transport Distance for Unsupervised Domain Adaptation
5. Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results;tarvainen;Proc ICONIP,2017
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