5 citations · 7 across the 4 of their papers we have counts for
5 papers
Making use of supercomputers in financial machine learning
Philippe Cotte, Pierre Lagier, Vincent Margot +1
This article is the result of a collaboration between Fujitsu and Advestis. This collaboration aims at refactoring and running an algorithm based on systematic exploration producin…
A New Method to Compare the Interpretability of Rule-based Algorithms
Vincent Margot, George Luta
Interpretability is becoming increasingly important for predictive model analysis. Unfortunately, as remarked by many authors, there is still no consensus regarding this notion. Th…
ESG investments: Filtering versus machine learning approaches
Carmine de Franco, Christophe Geissler, Vincent Margot +1
We designed a machine learning algorithm that identifies patterns between ESG profiles and financial performances for companies in a large investment universe. The algorithm consis…
Consistent Regression using Data-Dependent Coverings
Vincent Margot, Jean-Patrick Baudry, Frédéric Guilloux +1
In this paper, we introduce a novel method to generate interpretable regression function estimators. The idea is based on called data-dependent coverings. The aim is to extract fro…
Rule Induction Partitioning Estimator
Vincent Margot, Jean-Patrick Baudry, Frederic Guilloux +1
RIPE is a novel deterministic and easily understandable prediction algorithm developed for continuous and discrete ordered data. It infers a model, from a sample, to predict and to…