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Mar, 2019
基于图聚类的低秩核学习
Low-rank Kernel Learning for Graph-based Clustering
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Zhao Kang, Liangjian Wen, Wenyu Chen, Zenglin Xu
TL;DR
通过将图构建和核学习统一框架，可以通过彼此迭代的方式增强图及共识核，而我们提出了一种学习低秩核矩阵的方法，从候选核之间的邻域中寻找最优核矩阵，进而解决了现有多核学习算法中的一些问题，并得到了验证。
Abstract
Constructing the adjacency graph is fundamental to
graph-based clustering
.
graph learning
in kernel space has shown impressive performance on a number of benchmark data sets. However, its performance is largely d
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