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    政大機構典藏 > 理學院 > 應用數學系 > 期刊論文 >  Item 140.119/129521
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/129521

    Title: Tensor Decomposition for Dimension Reduction
    Authors: 黃子銘
    Huang, Su-Yun
    Huang, Tzee-Ming
    Cheng, Yu-Hsiang
    Contributors: 統計系
    Date: 2019-07
    Issue Date: 2020-04-28 13:46:38 (UTC+8)
    Abstract: Tensor data are data with multiway array structure. They are often very high dimensional and are routinely encountered in many scientific fields. Dimension reduction is the technique of reducing the number of underlying variables for compressed data representation and for model parsimony. Tensor dimension reduction aims for reducing the tensor data dimension while keeping data's tensor structure.
    Relation: Wiley Interdisciplinary Reviews: Computational Statistics,12:2
    Data Type: article
    DOI 連結: https://doi.org/10.1002/wics.1482
    DOI: 10.1002/wics.1482
    Appears in Collections:[應用數學系] 期刊論文

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