Robust Kernelized Multiview Self-Representation for Subspace Clustering

    IEEE transactions on neural networks and learning systems, pp. 1-14, 2020.

    Cited by: 0|Bibtex|Views58|Links
    WOS

    Abstract:

    In this article, we propose a multiview self-representation model for nonlinear subspaces clustering. By assuming that the heterogeneous features lie within the union of multiple linear subspaces, the recent multiview subspace learning methods aim to capture the complementary and consensus from multiple views to boost the performance. How...More

    Code:

    Data:

    Your rating :
    0

     

    Tags
    Comments