Neural network integral representations with the ReLU activation
function
Mathematical and Scientific Machine Learning (MSML), 2019
Abstract
We derive a formula for neural network integral representations on the sphere with the ReLU activation function under the finite norm (with respect to Lebesgue measure on the sphere) assumption on the outer weights. In one dimensional case, we further solve via a closed-form formula all possible such representations. Additionally, in this case our formula allows one to explicitly solve the least norm neural network representation for a given function.
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