Local and global regularized sparse coding for data representation

Volume: 175, Pages: 188 - 197
Published: Jan 1, 2016
Abstract
Recently, sparse coding has been widely adopted for data representation in real-world applications. In order to consider the geometric structure of data, we propose a novel method, local and global regularized sparse coding (LGSC), for data representation. LGSC not only models the global geometric structure by a global regression regularizer, but also takes into account the manifold structure using a local regression regularizer. Compared with...
Paper Details
Title
Local and global regularized sparse coding for data representation
Published Date
Jan 1, 2016
Volume
175
Pages
188 - 197
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