Structured Sparsity of Convolutional Neural Networks via Nonconvex Sparse Group Regularization

Structured Sparsity of Convolutional Neural Networks via Nonconvex Sparse Group Regularization

Convolutional neural networks (CNN) have been hugely successful recently with superior accuracy and performance in various imaging applications, such as classification, object detection, and segmentation. However, a highly accurate CNN model requires millions of parameters to be trained and utilized...

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Bibliographic Details
Main Authors: Kevin Bui, Fredrick Park, Shuai Zhang, Yingyong Qi, Jack Xin
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Applied Mathematics and Statistics
Subjects:
deep learning
sparsity
nonconvex optimization
sparse group lasso
feature selection
Online Access:https://www.frontiersin.org/articles/10.3389/fams.2020.529564/full

Internet

https://www.frontiersin.org/articles/10.3389/fams.2020.529564/full

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