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In this paper, we present a non-negative patch alignment framework (NPAF) to unify popular non-negative matrix factorization (NMF) related dimension reduction algorithms. It offers a new viewpoint to better understand the common property of different NMF algorithms. Although multiplicative update rule (MUR) can solve NPAF and is easy to implement, it converges slowly. Thus, we propose a fast gradient...
Dimension reduction algorithms have attracted a lot of attentions in face recognition because they can select a subset of effective and efficient discriminative features in the face images. Most of dimension reduction algorithms can not well model both the intra-class geometry and interclass discrimination simultaneously. In this paper, we introduce the Discriminative Hessian Eigenmaps (DHE), a novel...
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