A differentiable, scale-invariant sparsity regularizer based on the squared L1/L2 ratio is applied to neural network pruning and is claimed to beat prior L0 and L1 based methods.
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DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures
A differentiable, scale-invariant sparsity regularizer based on the squared L1/L2 ratio is applied to neural network pruning and is claimed to beat prior L0 and L1 based methods.