Generalized Incomplete Multiview Clustering With Flexible Locality Structure Diffusion

IEEE TRANSACTIONS ON CYBERNETICS, VOL. 51, NO. 1, JANUARY 2021

1)单个表示学习

2）共识表示学习

3）自适应多视图学习

特点：①引入指示矩阵G可以处理任意的缺失情况

②不但可以有效利用不完整数据中的局部信息用于表示学习，而且可以避免引入图拉普拉斯约束中的额外约束

③通过引入一些权重μ，可以自适应平衡不同视图的重要性

④通过UTU=I，基矩阵可以看作是特征学习的映射，可以处理out-of-sample data。

求解：

先转换为

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