82 citations · 196 across the 22 of their papers we have counts for
4 papers · 1 filter
On The Transferability of Deep-Q Networks
Matthia Sabatelli, Pierre Geurts
Transfer Learning (TL) is an efficient machine learning paradigm that allows overcoming some of the hurdles that characterize the successful training of deep neural networks, rangi…
From global to local MDI variable importances for random forests and when they are Shapley values
Antonio Sutera, Gilles Louppe, Van Anh Huynh-Thu +2
Random forests have been widely used for their ability to provide so-called importance measures, which give insight at a global (per dataset) level on the relevance of input variab…
Optimizing model-agnostic Random Subspace ensembles
Vân Anh Huynh-Thu, Pierre Geurts
This paper presents a model-agnostic ensemble approach for supervised learning. The proposed approach is based on a parametric version of Random Subspace, in which each base model…
Evaluating Local Explanations using White-box Models
Amir Hossein Akhavan Rahnama, Judith Butepage, Pierre Geurts +1
Evaluating explanation techniques using human subjects is costly, time-consuming and can lead to subjectivity in the assessments. To evaluate the accuracy of local explanations, we…