2 papers
cs.LG2020
Neural Rule Ensembles: Encoding Sparse Feature Interactions into Neural Networks
Gitesh Dawer, Yangzi Guo, Sida Liu +1
Artificial Neural Networks form the basis of very powerful learning methods. It has been observed that a naive application of fully connected neural networks to data with many irre…
stat.ML2018
Random Hinge Forest for Differentiable Learning
Nathan Lay, Adam P. Harrison, Sharon Schreiber +2
We propose random hinge forests, a simple, efficient, and novel variant of decision forests. Importantly, random hinge forests can be readily incorporated as a general component wi…