Multiple Flat Projections for Cross-Manifold Clustering
Multiple Flat Projections for Cross-Manifold Clustering
复制标题
用于跨流形聚类的多个平面投影
DOI：
10.1109/tcyb.2021.3050487
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发表时间：
2020-02
影响因子：
11.8
通讯作者：
Nai-Yang Deng
中科院分区：
文献类型：
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作者：
Lan Bai;Yuan-Hai Shao;Zhen Wang;Wei-Jie Chen;Nai-Yang Deng
跨界聚类是一个极端的挑战学习问题。由于在跨界问题中不满足低密度假设，因此许多传统的聚类方法未能发现跨势元结构。在本文中，我们专业
Cross-manifold clustering is an extreme challenge learning problem. Since the low-density hypothesis is not satisfied in cross-manifold problems, many traditional clustering methods failed to discover the cross-manifold structures. In this article, we propose multiple flat projections clustering (MFPC) for cross-manifold clustering. In our MFPC, the given samples are projected into multiple localized flats to discover the global structures of implicit manifolds. Thus, the intersected clusters are distinguished in various projection flats. In MFPC, a series of nonconvex matrix optimization problems is solved by a proposed recursive algorithm. Furthermore, a nonlinear version of MFPC is extended via kernel tricks to deal with a more complex cross-manifold learning situation. The synthetic tests show that our MFPC works on the cross-manifold structures well. Moreover, experimental results on the benchmark datasets and object tracking videos show excellent performance of our MFPC compared with some state-of-the-art manifold clustering methods.
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影响因子：
2.2
作者：
Bo Wen;Xiaojun Chen;Ting Kei Pong
通讯作者：
Bo Wen;Xiaojun Chen;Ting Kei Pong
DOI：
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发表时间：
--
期刊：
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影响因子：
--
作者：
通讯作者：
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影响因子：
8.1
作者：
Peng, Xinjun;Xu, Dong;Chen, Dongjing
通讯作者：
Chen, Dongjing
DOI：
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发表时间：
1996
期刊：
--
影响因子：
--
作者：
C. Merz
通讯作者：
C. Merz
影响因子：
6
作者：
Zhimin Yang;Yan-Ru Guo;Chunna Li;Y. Shao
通讯作者：
Zhimin Yang;Yan-Ru Guo;Chunna Li;Y. Shao