Taxonomy of Saliency Metrics for Channel Pruning

Taxonomy of Saliency Metrics for Channel Pruning

Pruning unimportant parameters can allow deep neural networks (DNNs) to reduce their heavy computation and memory requirements. A <italic>saliency metric</italic> estimates which parameters can be safely pruned with little impact on the classification performance of the DNN. Many salienc...

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Bibliographic Details
Main Authors: Kaveena Persand, Andrew Anderson, David Gregg
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Machine learning
convolution neural networks
pruning
saliency metric
model compression
Online Access:https://ieeexplore.ieee.org/document/9524570/

Internet

https://ieeexplore.ieee.org/document/9524570/

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