82 citations · 196 across the 22 of their papers we have counts for
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cs.LG2019★ 2 cited
Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms
Matthia Sabatelli, Gilles Louppe, Pierre Geurts +1
This paper makes one step forward towards characterizing a new family of \textit{model-free} Deep Reinforcement Learning (DRL) algorithms. The aim of these algorithms is to jointly…
stat.ML2019★ 7 cited
Gradient tree boosting with random output projections for multi-label classification and multi-output regression
Arnaud Joly, Louis Wehenkel, Pierre Geurts
In many applications of supervised learning, multiple classification or regression outputs have to be predicted jointly. We consider several extensions of gradient boosting to addr…