Semi-supervised domain adaptation with subspace learning for visual recognition

• Main Authors: YAO, Ting, PAN, Yingwei, NGO, Chong-wah, LI, Houqiang, MEI, Tao
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6465; https://ink.library.smu.edu.sg/context/sis_research/article/7468/viewcontent/Yao_Semi_Supervised_Domain_Adaptation_2015_CVPR_paper.pdf
• Institution: Singapore Management University

In many real-world applications, we are often facing the problem of cross domain learning, i.e., to borrow the labeled data or transfer the already learnt knowledge from a source domain to a target domain. However, simply applying existing source data or knowledge may even hurt the performance, espe...