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Manifold regularized techniques have been extensively exploited in unsupervised learning like matrix factorization whose performance is heavily affected by the underlying graph regularization. However, there exist no principled ways to select reasonable graphs under the matrix decomposition setting, particularly in multiple heterogeneous graph sources. In this paper, we deal with the issue of searching...
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