Discriminative Orthogonal Nonnegative matrix factorization with flexibility for data representation
作者:
Highlights:
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摘要
•We propose the Discriminative Orthogonal NMF method for data representation.•Our method respects the locally geometrical structure of the data.•Our method employs the global discriminant information of the data.•We make the method be more adaptive with flexible orthogonality regularization.•Extensive experiments suggest the superiority of the proposed method.
论文关键词:Nonnegative matrix factorization,Flexible orthogonality,Manifold discriminant learning,Data representation
论文评审过程:Author links open overlay panelPingLiaPersonEnvelopeJiajunBuaYiYangbRongrongJicChunChenaDengCaid
论文官网地址:https://doi.org/10.1016/j.eswa.2013.08.026