A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks
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To fit sparse linear associations, a LASSO sparsity inducing penalty with a single hyperparameter provably allows to recover the important features (needles) with high probability in certain regimes even if the sample size is smaller than the dimension of the ... ...
