17 citations · 32 across the 8 of their papers we have counts for
9 papers
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…
Cyber-physical risk modeling with imperfect cyber-attackers
Efthymios Karangelos, Louis Wehenkel
We model the risk posed by a malicious cyber-attacker seeking to induce grid insecurity by means of a load redistribution attack, while explicitly acknowledging that such an actor…
Bayesian estimates of transmission line outage rates that consider line dependencies
Kai Zhou, James R. Cruise, Chris J. Dent +4
Transmission line outage rates are fundamental to power system reliability analysis. Line outages are infrequent, occurring only about once a year, so outage data are limited. We p…
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…
Chance-Constrained Outage Scheduling using a Machine Learning Proxy
Gal Dalal, Elad Gilboa, Shie Mannor +1
Outage scheduling aims at defining, over a horizon of several months to years, when different components needing maintenance should be taken out of operation. Its objective is to m…
Random Subspace with Trees for Feature Selection Under Memory Constraints
Antonio Sutera, Célia Châtel, Gilles Louppe +2
Dealing with datasets of very high dimension is a major challenge in machine learning. In this paper, we consider the problem of feature selection in applications where the memory…