28 citations · 97 across the 16 of their papers we have counts for
17 papers
SecuLEx: a Secure Limit Exchange Market for Dynamic Operating Envelopes
Maurizio Vassallo, Adrien Bolland, Alireza Bahmanyar +9
Distributed energy resources (DERs) are transforming power networks, challenging traditional operational methods, and requiring new coordination mechanisms. To address this challen…
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…
Unit Commitment using Nearest Neighbor as a Short-Term Proxy
Gal Dalal, Elad Gilboa, Shie Mannor +1
We devise the Unit Commitment Nearest Neighbor (UCNN) algorithm to be used as a proxy for quickly approximating outcomes of short-term decisions, to make tractable hierarchical lon…
Context-dependent feature analysis with random forests
Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu +2
In many cases, feature selection is often more complicated than identifying a single subset of input variables that would together explain the output. There may be interactions tha…
Whither probabilistic security management for real-time operation of power systems ?
Efthymios Karangelos, Patrick Panciatici, Louis Wehenkel
This paper investigates the stakes of introducing probabilistic approaches for the management of power system's security. In real-time operation, the aim is to arbitrate in a ratio…
Classifying pairs with trees for supervised biological network inference
Marie Schrynemackers, Louis Wehenkel, M. Madan Babu +1
Networks are ubiquitous in biology and computational approaches have been largely investigated for their inference. In particular, supervised machine learning methods can be used t…
Random forests with random projections of the output space for high dimensional multi-label classification
Arnaud Joly, Pierre Geurts, Louis Wehenkel
We adapt the idea of random projections applied to the output space, so as to enhance tree-based ensemble methods in the context of multi-label classification. We show how learning…
On the Construction of the Inclusion Boundary Neighbourhood for Markov Equivalence Classes of Bayesian Network Structures
Vincent Auvray, Louis Wehenkel
The problem of learning Markov equivalence classes of Bayesian network structures may be solved by searching for the maximum of a scoring metric in a space of these classes. This p…
Optimized Look-Ahead Tree Policies: A Bridge Between Look-Ahead Tree Policies and Direct Policy Search
Tobias Jung, Louis Wehenkel, Damien Ernst +1
Direct policy search (DPS) and look-ahead tree (LT) policies are two widely used classes of techniques to produce high performance policies for sequential decision-making problems.…
Meta-Learning of Exploration/Exploitation Strategies: The Multi-Armed Bandit Case
Francis Maes, Damien Ernst, Louis Wehenkel
The exploration/exploitation (E/E) dilemma arises naturally in many subfields of Science. Multi-armed bandit problems formalize this dilemma in its canonical form. Most current res…
Learning Inclusion-Optimal Chordal Graphs
Vincent Auvray, Louis Wehenkel
Chordal graphs can be used to encode dependency models that are representable by both directed acyclic and undirected graphs. This paper discusses a very simple and efficient algor…
Scenario trees and policy selection for multistage stochastic programming using machine learning
Boris Defourny, Damien Ernst, Louis Wehenkel
We propose a hybrid algorithmic strategy for complex stochastic optimization problems, which combines the use of scenario trees from multistage stochastic programming with machine…