Variational Convolutional Neural Network Pruning
Published: Jun 1, 2019
Abstract
We propose a variational Bayesian scheme for pruning convolutional neural networks in channel level. This idea is motivated by the fact that deterministic value based pruning methods are inherently improper and unstable. In a nutshell, variational technique is introduced to estimate distribution of a newly proposed parameter, called channel saliency, based on this, redundant channels can be removed from model via a simple criterion. The...
Paper Details
Title
Variational Convolutional Neural Network Pruning
Published Date
Jun 1, 2019
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