20 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- J. Darmont2 profiles38 · h 23
- Omar Boussaïd2 profiles8 · h 21
- Hadj Mahboubi7 · h 9
- Sabine Loudcher2 profiles7 · h 14
- Cécile Favre2 profiles6 · h 14
- F. Bentayeb6 · h 17
- Kamel Aouiche2 profiles6 · h 11
- Irène Gannaz2 profiles3 · h 7
- Jairo Cugliari3 profiles3 · h 9
- Jérôme Darmont3 · h 1
- Muhammad Fahad2 profiles3 · h 2
- Pegdwendé N. Sawadogo2 profiles3 · h 4
- Entrepôts, Représentation et Ingénierie des ConnaissancesFR12 papers
- Lyon 1 UniversitéFR9 papers
- Université Lumière Lyon 2FR6 papers
- Agrosystèmes tropicauxGP1 paper
- Archéologie et ArchéométrieFR1 paper
- Australian National UniversityAU1 paper
- Centre Inria de SaclayFR1 paper
- Centre Max WeberFR1 paper
- Essilor (France)FR1 paper
- Institut Camille JordanFR1 paper
- Institut dal Dicziunari Rumantsch GrischunCH1 paper
- Institut de Recherche en Informatique de ToulouseFR1 paper
4 papers · 1 filter
User Profiles of Sleep Disorder Sufferers: Towards Explainable Clustering and Differential Variable Analysis
Sifeddine Sellami, Juba Agoun, Lamia Yessad +1
Sleep disorders have a major impact on patients' health and quality of life, but their diagnosis remains complex due to the diversity of symptoms. Today, technological advances, co…
Pr{é}diction optimale pour un mod{è}le ordinal {à} covariables fonctionnelles
Simón Weinberger, Jairo Cugliari, Aurélie Le Cain
We present a prediction framework for ordinal models: we introduce optimal predictions using loss functions and give the explicit form of the Least-Absolute-Deviation prediction fo…
Policy gradient methods for ordinal policies
Simón Weinberger, Jairo Cugliari
In reinforcement learning, the softmax parametrization is the standard approach for policies over discrete action spaces. However, it fails to capture the order relationship betwee…
FedHQ: Hybrid Runtime Quantization for Federated Learning
Zihao Zheng, Ziyao Wang, Xiuping Cui +6
Federated Learning (FL) is a decentralized model training approach that preserves data privacy but struggles with low efficiency. Quantization, a powerful training optimization tec…