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    A Novel Transfer Learning Method Based on Common Space Mapping and Weighted Domain Matching

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    Type
    Conference Paper
    Authors
    Liang, Ru-Ze cc
    Xie, Wei
    Li, Weizhi
    Wang, Hongqi
    Wang, Jim Jing-Yan
    Taylor, Lisa
    KAUST Department
    Material Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2017-01-17
    Online Publication Date
    2017-01-17
    Print Publication Date
    2016-11
    Permanent link to this record
    http://hdl.handle.net/10754/622934
    
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    Abstract
    In this paper, we propose a novel learning framework for the problem of domain transfer learning. We map the data of two domains to one single common space, and learn a classifier in this common space. Then we adapt the common classifier to the two domains by adding two adaptive functions to it respectively. In the common space, the target domain data points are weighted and matched to the target domain in term of distributions. The weighting terms of source domain data points and the target domain classification responses are also regularized by the local reconstruction coefficients. The novel transfer learning framework is evaluated over some benchmark cross-domain data sets, and it outperforms the existing state-of-the-art transfer learning methods.
    Citation
    Liang R-Z, Xie W, Li W, Wang H, Wang JJ-Y, et al. (2016) A Novel Transfer Learning Method Based on Common Space Mapping and Weighted Domain Matching. 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI). Available: http://dx.doi.org/10.1109/ICTAI.2016.0053.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)
    DOI
    10.1109/ICTAI.2016.0053
    arXiv
    arXiv:1608.04581
    Additional Links
    http://ieeexplore.ieee.org/document/7814613/
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICTAI.2016.0053
    Scopus Count
    Collections
    Conference Papers; Physical Science and Engineering (PSE) Division; Material Science and Engineering Program

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