For semiparametric M-estimation with overparameterized ReLU networks, the gradient-flow estimator achieves minimax nonparametric rates and root-n-consistent, asymptotically normal estimates of the finite-dimensional parameter.
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Semiparametric M-estimation with overparameterized neural networks
For semiparametric M-estimation with overparameterized ReLU networks, the gradient-flow estimator achieves minimax nonparametric rates and root-n-consistent, asymptotically normal estimates of the finite-dimensional parameter.