Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization
Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization
LASSO regularization is a popular regression tool to enhance the prediction accuracy of statistical models by performing variable selection through the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> penalty, initially formulated for the linear model and its variants. In this paper, the territory of LASSO is extended to two-layer ReLU …