2 papers
stat.ME2024
Nearly Optimal Learning using Sparse Deep ReLU Networks in Regularized Empirical Risk Minimization with Lipschitz Loss
Ke Huang, Mingming Liu, Shujie Ma
We propose a sparse deep ReLU network (SDRN) estimator of the regression function obtained from regularized empirical risk minimization with a Lipschitz loss function. Our framewor…
stat.ML2024
Generalization and Risk Bounds for Recurrent Neural Networks
Xuewei Cheng, Ke Huang, Shujie Ma
Recurrent Neural Networks (RNNs) have achieved great success in the prediction of sequential data. However, their theoretical studies are still lagging behind because of their comp…