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Sparse Switchable Normalization
Introduced by Wenqi Shao et al. in SSN: Learning Sparse Switchable Normalization via SparsestMax
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Sparse Switchable Normalization (SSN) is a variant on Switchable Normalization where the importance ratios are constrained to be sparse. Unlike ℓ₁ and ℓ₀ constraints that impose difficulties in optimization, the constrained optimization problem is turned into feed-forward computation through SparseMax, which is a sparse version of softmax.
Papers archive 2025-07-28
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SSN: Learning Sparse Switchable Normalization via SparsestMax 9 Mar 2019 · 1 repository · arXiv:1903.03793
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