Distance Metric Learning A Comprehensive Survey Bibtex Bibliography

  • 2018
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    Nannan Wang, Xinbo Gao, Dacheng Tao, Heng Yang, Xuelong Li:
    Facial feature point detection: A comprehensive survey.Neurocomputing275: 50-65 (2018)

  • [j381]

    Qiang Zhang, Yi Liu, Rick S. Blum, Jungong Han, Dacheng Tao:
    Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: A review.Information Fusion40: 57-75 (2018)

  • [j380]

    Xinke Shen, Tao Liu, Dacheng Tao, Yubo Fan, Jicong Zhang, Shuyu Li, Jiyang Jiang, Wanlin Zhu, Yilong Wang, Yongjun Wang, Henry Brodaty, Perminder S. Sachdev, Wei Wen:
    Variation in longitudinal trajectories of cortical sulci in normal elderly.NeuroImage166: 1-9 (2018)

  • [j379]

    Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan:
    Fast Supervised Discrete Hashing.IEEE Trans. Pattern Anal. Mach. Intell.40(2): 490-496 (2018)

  • [j378]

    Cheng Deng, Xianglong Liu, Chao Li, Dacheng Tao:
    Active multi-kernel domain adaptation for hyperspectral image classification.Pattern Recognition77: 306-315 (2018)

  • [j377]

    Yue Zhao, Xinge You, Shujian Yu, Chang Xu, Wei Yuan, Xiao-Yuan Jing, Taiping Zhang, Dacheng Tao:
    Multi-view manifold learning with locality alignment.Pattern Recognition78: 154-166 (2018)

  • [j376]

    Tao Mei, Lusong Li, Xinmei Tian, Dacheng Tao, Chong-Wah Ngo:
    PageSense: Toward Stylewise Contextual Advertising via Visual Analysis of Web Pages.IEEE Trans. Circuits Syst. Video Techn.28(1): 254-266 (2018)

  • [j375]

    Lefei Zhang, Qian Zhang, Bo Du, Xin Huang, Yuan Yan Tang, Dacheng Tao:
    Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.IEEE Trans. Cybernetics48(1): 16-28 (2018)

  • [j374]

    Chen Gong, Tongliang Liu, Yuanyan Tang, Jian Yang, Jie Yang, Dacheng Tao:
    A Regularization Approach for Instance-Based Superset Label Learning.IEEE Trans. Cybernetics48(3): 967-978 (2018)

  • [j373]

  • Title: Distance Metric Learning for Aspect Phrase Grouping

    Authors:Shufeng Xiong, Yue Zhang, Donghong Ji, Yinxia Lou

    (Submitted on 29 Apr 2016 (v1), last revised 30 Oct 2016 (this version, v2))

    Abstract: Aspect phrase grouping is an important task in aspect-level sentiment analysis. It is a challenging problem due to polysemy and context dependency. We propose an Attention-based Deep Distance Metric Learning (ADDML) method, by considering aspect phrase representation as well as context representation. First, leveraging the characteristics of the review text, we automatically generate aspect phrase sample pairs for distant supervision. Second, we feed word embeddings of aspect phrases and their contexts into an attention-based neural network to learn feature representation of contexts. Both aspect phrase embedding and context embedding are used to learn a deep feature subspace for measure the distances between aspect phrases for K-means clustering. Experiments on four review datasets show that the proposed method outperforms state-of-the-art strong baseline methods.

    Submission history

    From: Shufeng Xiong [view email]
    [v1] Fri, 29 Apr 2016 02:44:02 GMT (54kb)
    [v2] Sun, 30 Oct 2016 02:09:15 GMT (84kb)

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