25 citations · 39 across the 12 of their papers we have counts for
6 papers · 1 filter
Bilevel Optimization for Feature Selection in the Data-Driven Newsvendor Problem
Breno Serrano, Stefan Minner, Maximilian Schiffer +1
We study the feature-based newsvendor problem, in which a decision-maker has access to historical data consisting of demand observations and exogenous features. In this setting, we…
Optimal Decision Diagrams for Classification
Alexandre M. Florio, Pedro Martins, Maximilian Schiffer +2
Decision diagrams for classification have some notable advantages over decision trees, as their internal connections can be determined at training time and their width is not bound…
Optimal Counterfactual Explanations in Tree Ensembles
Axel Parmentier, Thibaut Vidal
Counterfactual explanations are usually generated through heuristics that are sensitive to the search's initial conditions. The absence of guarantees of performance and robustness…
Semi-Supervised Clustering with Inaccurate Pairwise Annotations
Daniel Gribel, Michel Gendreau, Thibaut Vidal
Pairwise relational information is a useful way of providing partial supervision in domains where class labels are difficult to acquire. This work presents a clustering model that…
Born-Again Tree Ensembles
Thibaut Vidal, Toni Pacheco, Maximilian Schiffer
The use of machine learning algorithms in finance, medicine, and criminal justice can deeply impact human lives. As a consequence, research into interpretable machine learning has…
HG-means: A scalable hybrid genetic algorithm for minimum sum-of-squares clustering
Daniel Gribel, Thibaut Vidal
Minimum sum-of-squares clustering (MSSC) is a widely used clustering model, of which the popular K-means algorithm constitutes a local minimizer. It is well known that the solution…