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20082025
most citedLarge deviations for the Boussinesq Equations under Random Influences

132 citations

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10 papers · 1 filter

stat.ML2025

Fairness Meets Privacy: Integrating Differential Privacy and Demographic Parity in Multi-class Classification

Lilian Say, Christophe Denis, Rafael Pinot

The increasing use of machine learning in sensitive applications demands algorithms that simultaneously preserve data privacy and ensure fairness across potentially sensitive sub-p…

stat.ML2025

Set to Be Fair: Demographic Parity Constraints for Set-Valued Classification

Eyal Cohen, Christophe Denis, Mohamed Hebiri

Set-valued classification is used in multiclass settings where confusion between classes can occur and lead to misleading predictions. However, its application may amplify discrimi…

stat.ML2025

Empirical risk minimization algorithm for multiclass classification of S.D.E. paths

Christophe Denis, Eddy Ella Mintsa

We address the multiclass classification problem for stochastic diffusion paths, assuming that the classes are distinguished by their drift functions, while the diffusion coefficie…

stat.ML2017★ 11 cited

Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL

Marco Corneli, Pierre Latouche, Fabrice Rossi

We develop a model in which interactions between nodes of a dynamic network are counted by non homogeneous Poisson processes. In a block modelling perspective, nodes belong to hidd…

stat.ML2015★ 36 cited

Using the Mean Absolute Percentage Error for Regression Models

Arnaud De Myttenaere, Boris Golden, Bénédicte Le Grand +1

We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We show that finding the best model under…

stat.ML2014★ 6 cited

A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation

Tsirizo Rabenoro, Jérôme Lacaille, Marie Cottrell +1

Aircraft engine manufacturers collect large amount of engine related data during flights. These data are used to detect anomalies in the engines in order to help companies optimize…