Model-based sparse coding beyond Gaussian independent model
Volume: 166, Pages: 107336 - 107336
Published: Feb 1, 2022
Abstract
Sparse coding aims to model data vectors as sparse linear combinations of basis elements, but a majority of related studies are restricted to continuous data without spatial or temporal structure. A new model-based sparse coding (MSC) method is proposed to provide an effective and flexible framework for learning features from different data types: continuous, discrete, or categorical, and modeling different types of correlations: spatial or...
Paper Details
Title
Model-based sparse coding beyond Gaussian independent model
Published Date
Feb 1, 2022
Volume
166
Pages
107336 - 107336
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