Achieving adversarial robustness via sparsity
Achieving adversarial robustness via sparsity
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Publisher
New York: Springer US
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Language
English
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Publisher
New York: Springer US
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Contents
Network pruning has been known to produce compact models without much accuracy degradation. However, how the pruning process affects a network’s robustness and the working mechanism behind remain unresolved. In this work, we theoretically prove that the sparsity of network weights is closely associated with model robustness. Through experiments on...
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Full title
Achieving adversarial robustness via sparsity
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TN_cdi_proquest_journals_2642624367
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2642624367
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ISSN
0885-6125
E-ISSN
1573-0565
DOI
10.1007/s10994-021-06049-9
