Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

The data science doctor continues his exploration of techniques used to reduce the likelihood of model overfitting, caused by training a neural network for too many iterations. Regularization is a ...

We study the consistency of the estimator in a spatial regression with partial differential equation (PDE) regularization. This new smoothing technique allows us to accurately estimate spatial fields ...