1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2020★ 1 cited
Learning Representations for Axis-Aligned Decision Forests through Input Perturbation
Sebastian Bruch, Jan Pfeifer, Mathieu Guillame-bert
Axis-aligned decision forests have long been the leading class of machine learning algorithms for modeling tabular data. In many applications of machine learning such as learning-t…
cs.LG2016
Batched Lazy Decision Trees
Mathieu Guillame-Bert, Artur Dubrawski
We introduce a batched lazy algorithm for supervised classification using decision trees. It avoids unnecessary visits to irrelevant nodes when it is used to make predictions with…