Structured Bayesian Compression for Deep Neural Networks Based on the Turbo-VBI Approach

With the growth of neural network size, model compression has attracted increasing interest in recent research. As one of the most common techniques, pruning has been studied for a long time. By exploiting the structured sparsity of the neural network, existing methods can prune neurons instead of i...

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Vydané v:	IEEE transactions on signal processing Ročník 71; s. 1 - 16
Hlavní autori:	Xia, Chengyu, Tsang, Danny H. K., Lau, Vincent K. N.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Artificial neural networks Bayes methods Bayesian analysis Biological neural networks Complexity Deep neural networks group sparsity model compression Network topology Neural networks Neurons pruning Sparse matrices Sparsity Topology Training
ISSN:	1053-587X, 1941-0476
On-line prístup:	Získať plný text
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