2018
Regularization Learning Networks: Deep Learning for Tabular Datasets
NeurIPS 2018poster
Despite their impressive performance, Deep Neural Networks (DNNs) typically underperform Gradient Boosting Trees (GBTs) on many tabular-dataset learning tasks. We propose that applying a different regularization coefficient to each weight might boost the performance of DNNs by allowing them to make…