scholarly journals Multiple Kernel Clustering With Global and Local Structure Alignment

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 77911-77920 ◽  
Author(s):  
Chuanli Wang ◽  
En Zhu ◽  
Xinwang Liu ◽  
Long Gao ◽  
Jianping Yin ◽  
...  
Keyword(s):  
Local Structure ◽  
Structure Alignment ◽  
Multiple Kernel ◽  
Kernel Clustering ◽  
Multiple Kernel Clustering ◽  
Global And Local

scholarly journals Clustering-Induced Adaptive Structure Enhancing Network for Incomplete Multi-View Data

2021 ◽  
Author(s):  
Zhe Xue ◽  
Junping Du ◽  
Changwei Zheng ◽  
Jie Song ◽  
Wenqi Ren ◽  
...  
Keyword(s):  
Data Structure ◽  
Local Structure ◽  
Data Clustering ◽  
Superior Performance ◽  
Multiple Kernel ◽  
Kernel Clustering ◽  
Adaptive Structure ◽  
Benchmark Datasets ◽  
Multiple Kernel Clustering ◽  
Global And Local

Incomplete multi-view clustering aims to cluster samples with missing views, which has drawn more and more research interest. Although several methods have been developed for incomplete multi-view clustering, they fail to extract and exploit the comprehensive global and local structure of multi-view data, so their clustering performance is limited. This paper proposes a Clustering-induced Adaptive Structure Enhancing Network (CASEN) for incomplete multi-view clustering, which is an end-to-end trainable framework that jointly conducts multi-view structure enhancing and data clustering. Our method adopts multi-view autoencoder to infer the missing features of the incomplete samples. Then, we perform adaptive graph learning and graph convolution on the reconstructed complete multi-view data to effectively extract data structure. Moreover, we use multiple kernel clustering to integrate the global and local structure for clustering, and the clustering results in turn are used to enhance the data structure. Extensive experiments on several benchmark datasets demonstrate that our method can comprehensively obtain the structure of incomplete multi-view data and achieve superior performance compared to the other methods.

Multiple kernel clustering with corrupted kernels

2017 ◽  
Vol 267 ◽  
pp. 447-454 ◽  
Author(s):  
Teng Li ◽  
Yong Dou ◽  
Xinwang Liu ◽  
Yang Zhao ◽  
Qi Lv
Keyword(s):  
Multiple Kernel ◽  
Kernel Clustering ◽  
Multiple Kernel Clustering

Simultaneous learning coefficient matrix and affinity graph for multiple kernel clustering

2021 ◽  
Vol 547 ◽  
pp. 289-306
Author(s):  
Zhenwen Ren ◽  
Haoyun Lei ◽  
Quansen Sun ◽  
Chao Yang
Keyword(s):  
Coefficient Matrix ◽  
Multiple Kernel ◽  
Kernel Clustering ◽  
Multiple Kernel Clustering

Multiple kernel clustering with pure graph learning scheme

2020 ◽  
Author(s):  
Xingfeng Li ◽  
Zhenwen Ren ◽  
Haoyun Lei ◽  
Yuqing Huang ◽  
Quansen Sun
Keyword(s):  
Graph Learning ◽  
Multiple Kernel ◽  
Learning Scheme ◽  
Kernel Clustering ◽  
Multiple Kernel Clustering

scholarly journals A Fast and Effective Multiple Kernel Clustering Method on Incomplete Data

2021 ◽  
Vol 67 (1) ◽  
pp. 267-284
Author(s):  
Lingyun Xiang ◽  
Guohan Zhao ◽  
Qian Li ◽  
Gwang-jun Kim ◽  
Osama Alfarraj ◽  
...  
Keyword(s):  
Incomplete Data ◽  
Clustering Method ◽  
Multiple Kernel ◽  
Kernel Clustering ◽  
Multiple Kernel Clustering

Optimal Neighborhood Multiple Kernel Clustering with Adaptive Local Kernels

2021 ◽  
pp. 1-1 ◽  
Author(s):  
Jiyuan Liu ◽  
Xinwang Liu ◽  
Jian Xiong ◽  
Qing Liao ◽  
Sihang Zhou ◽  
...  
Keyword(s):  
Multiple Kernel ◽  
Kernel Clustering ◽  
Multiple Kernel Clustering
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