Learning Sparse Convolutional Neural Network via Quantization With Low Rank Regularization

Learning Sparse Convolutional Neural Network via Quantization With Low Rank Regularization

With the refinement of tasks in artificial intelligence, bringing in exponential level increments in computation cost and storage. Therefore, the augment of computation resource for complicated neural networks severely hinders their applications on limited-power devices in recent years. As a result,...

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Bibliographic Details
Main Authors: Xin Long, Zongcheng Ben, Xiangrong Zeng, Yan Liu, Maojun Zhang, Dianle Zhou
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Convolutional neural network (CNN)
weight quantization
spectral regularization
sparsity
visualization
channel pruning
Online Access:https://ieeexplore.ieee.org/document/8692364/

Internet

https://ieeexplore.ieee.org/document/8692364/

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