Kernel Regularized Nonlinear Dictionary Learning for Sparse Coding

Volume: 49, Issue: 4, Pages: 766 - 775
Published: Apr 1, 2019
Abstract
For most sparse coding methods, data samples are first encoded as hand-crafted features, followed by another separate learning step that generates dictionary and sparse codes. However, such feature representations may not be optimally compatible with the learning process, thus producing suboptimal results. In this paper, we propose a new architecture for nonlinear dictionary learning with sparse coding, in which samples are mapped into sparse...
Paper Details
Title
Kernel Regularized Nonlinear Dictionary Learning for Sparse Coding
Published Date
Apr 1, 2019
Volume
49
Issue
4
Pages
766 - 775
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