Multiple Kernel <italic>k</italic>-Means With Low-Rank Neighborhood Kernel

Multiple Kernel <italic>k</italic>-Means With Low-Rank Neighborhood Kernel

Multiple kernel clustering algorithms achieve promising performances by exploring the complementary information from kernel matrices corresponding to each data view. Most of the existing methods aim to construct a consensus kernel for the afterward clustering. However, they ignore that the desired k...

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Bibliographic Details
Main Authors: Qiyuan Ou, Long Gao, En Zhu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Clustering algorithms
multiple kernel clustering
multiple view clustering
Online Access:https://ieeexplore.ieee.org/document/9274380/

Internet

https://ieeexplore.ieee.org/document/9274380/

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