Sparse Switchable Normalization
Sparse Switchable Normalization
**Sparse Switchable Normalization (SSN)** is a variant on [Switchable Normalization](https://paperswithcode.com/method/switchable-normalization) where the importance ratios are constrained to be sparse. Unlike $\ell_1$ and $\ell_0$ constraints that impose difficulties in optimization, the constrained optimization problem is turned into feed-forward computation through [SparseMax](https://paperswithcode.com/method/sparsemax), which is a sparse version of [softmax](https://paperswithcode.com/method/softmax).
SSN: Learning Sparse Switchable Normalization via SparsestMax
https://paperswithcode.com/paper/ssn-learning-sparse-switchable-normalization
SSN: Learning Sparse Switchable Normalization via SparsestMax