Paper ID: 2311.08845

Statistical learning by sparse deep neural networks

Felix Abramovich

We consider a deep neural network estimator based on empirical risk minimization with l_1-regularization. We derive a general bound for its excess risk in regression and classification (including multiclass), and prove that it is adaptively nearly-minimax (up to log-factors) simultaneously across the entire range of various function classes.

Submitted: Nov 15, 2023