Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices

IEEE Transactions on Neural Networks and Learning Systems(2017)

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摘要
Data encoded as symmetric positive definite (SPD) matrices frequently arise in many areas of computer vision and machine learning. While these matrices form an open subset of the Euclidean space of symmetric matrices, viewing them through the lens of non-Euclidean Riemannian (Riem) geometry often turns out to be better suited in capturing several desirable data properties. Inspired by the great su...
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关键词
Encoding,Geometry,Learning systems,Covariance matrices,Sparse matrices,Symmetric matrices,Dictionaries
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