8 citations · 8 across the 2 of their papers we have counts for
3 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★ 8 cited
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…
stat.ML2017
Generating Compact Tree Ensembles via Annealing
Gitesh Dawer, Yangzi Guo, Adrian Barbu
Tree ensembles are flexible predictive models that can capture relevant variables and to some extent their interactions in a compact and interpretable manner. Most algorithms for o…