298 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université de LilleFR364 papers
- Centre National de la Recherche ScientifiqueFR257 papers
- École Centrale de LilleFR212 papers
- Centre de Recherche en InformatiqueFR203 papers
- Université Paris-SaclayFR74 papers
- Institut d'Astrophysique SpatialeFR64 papers
- Sorbonne UniversitéFR59 papers
- Institut de Recherche en Astrophysique et PlanétologieFR58 papers
- Université Paris CitéFR57 papers
- Université Paris Sciences et LettresFR53 papers
- Ludwig-Maximilians-Universität MünchenDE52 papers
- CEA Paris-SaclayFR51 papers
7 papers · 2 filters
A Deep Neural Networks ensemble workflow from hyperparameter search to inference leveraging GPU clusters
Pierrick Pochelu, Serge G. Petiton, Bruno Conche
Automated Machine Learning with ensembling (or AutoML with ensembling) seeks to automatically build ensembles of Deep Neural Networks (DNNs) to achieve qualitative predictions. Ens…
Fusion of Physiological and Behavioural Signals on SPD Manifolds with Application to Stress and Pain Detection
Yujin WU, Mohamed Daoudi, Ali Amad +2
Existing multimodal stress/pain recognition approaches generally extract features from different modalities independently and thus ignore cross-modality correlations. This paper pr…
Learning Optimal Transport Between two Empirical Distributions with Normalizing Flows
Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais
Optimal transport (OT) provides effective tools for comparing and mapping probability measures. We propose to leverage the flexibility of neural networks to learn an approximate op…
How Biased are Your Features?: Computing Fairness Influence Functions with Global Sensitivity Analysis
Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel
Fairness in machine learning has attained significant focus due to the widespread application in high-stake decision-making tasks. Unregulated machine learning classifiers can exhi…
Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data
Batiste Le Bars, Aurélien Bellet, Marc Tommasi +2
One of the key challenges in decentralized and federated learning is to design algorithms that efficiently deal with highly heterogeneous data distributions across agents. In this…
Covid19 Reproduction Number: Credibility Intervals by Blockwise Proximal Monte Carlo Samplers
Gersende Fort, Barbara Pascal, Patrice Abry +1
Monitoring the Covid19 pandemic constitutes a critical societal stake that received considerable research efforts. The intensity of the pandemic on a given territory is efficiently…
Bregman Deviations of Generic Exponential Families
Sayak Ray Chowdhury, Patrick Saux, Odalric-Ambrym Maillard +1
We revisit the method of mixture technique, also known as the Laplace method, to study the concentration phenomenon in generic exponential families. Combining the properties of Bre…