Make \(\ell_1\) regularization effective in training sparse CNN

DOI10.1007/S10589-020-00202-1zbMath1480.90178arXiv1807.04222OpenAlexW3038359569MaRDI QIDQ782914

D. Kharzeev

Publication date: 29 July 2020

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1807.04222

zbMATH Keywords

sparse optimizationdual averaging\(\ell_1\) regularization

Mathematics Subject Classification ID

Stochastic programming (90C15)

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Uses Software

• ThiNet

Cites Work

• Primal-dual subgradient methods for convex problems
• Incremental proximal methods for large scale convex optimization
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• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Splitting Algorithms for the Sum of Two Nonlinear Operators
• Compressed sensing
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