Designing a Belief Function-Based Accessibility Indicator to Improve Web Browsing for Disabled People. - Jean-Christophe Dubois; Yolande Le Gall; Arnaud Martin 001 (Belief Functions, 2014)

Measuring the Expertise of Workers for Crowdsourcing Applications. - Jean-Christophe Dubois; Laetitia Gros; Mouloud Kharoune; Yolande Le Gall; Arnaud Martin 001; Zoltán Miklós 001; Hosna Ouni (EGC (best of volume), 2018)

Contributors profile modelization in crowdsourcing platforms. - Constance Thierry; Jean-Christophe Dubois; Yolande Le Gall; Arnaud Martin 001 (CoRR, 2018)

Modeling Uncertainty and Inaccuracy on Data from Crowdsourcing Platforms: MONITOR. - Constance Thierry; Jean-Christophe Dubois; Yolande Le Gall; Arnaud Martin 001 (ICTAI, 2019)

Modélisation de l'incertitude et de l'imprécision de données de crowdsourcing : MONITOR. - Constance Thierry; Jean-Christophe Dubois; Yolande Le Gall; Arnaud Martin 001 (EGC, 2020)

Validation of Smets' Hypothesis in the Crowdsourcing Environment. - Constance Thierry; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (BELIEF, 2021)

Evidential Nearest Neighbours in Active Learning. - Daniel Zhu; Arnaud Martin 001; Yolande Le Gall; Jean-Christophe Dubois; Vincent Lemaire 001 (IAL@PKDD/ECML, 2021)

Imperfect Labels with Belief Functions for Active Learning. - Arthur Hoarau; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (BELIEF, 2022)

Real Bird Dataset with Imprecise and Uncertain Values. - Constance Thierry; Arthur Hoarau; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (BELIEF, 2022)

Datasets with Rich Labels for Machine Learning. - Arthur Hoarau; Constance Thierry; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (FUZZ, 2023)

Modeling evolutionary responses in crowdsourcing MCQ using belief function theory. - Constance Thierry; Arnaud Martin 001; Yolande Le Gall; Jean-Christophe Dubois (KES, 2023)

Evidential uncertainties on rich labels for active learning. - Arthur Hoarau; Vincent Lemaire 001; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (CoRR, 2023)

Estimation of the qualification and behavior of a contributor and aggregation of his answers in a crowdsourcing context. - Constance Thierry; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (Expert Syst. Appl., 2023)

Evidential Random Forests. - Arthur Hoarau; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (Expert Syst. Appl., 2023)

A Mean Distance Between Elements of Same Class for Rich Labels. - Arthur Hoarau; Constance Thierry; Jean-Christophe Dubois; Yolande Le Gall (BELIEF, 2024)

Automated Hierarchical Conflict Reduction for Crowdsourced Annotation Tasks Using Belief Functions. - Constance Thierry; David Gross-Amblard; Yolande Le Gall; Jean-Christophe Dubois (BELIEF, 2024)

Méthode crédibiliste pour l'extraction d'incertitudes sans dépendance aux observations. - Arthur Hoarau; Vincent Lemaire 001; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (EGC, 2024)

Quantifying and Leveraging Uncertain and Imprecise Answers in Multiple Choice Questionnaires for Crowdsourcing: Quantifier et exploiter des réponses incertaines et imprécises dans des questionnaires à choix multiples pour le crowdsourcing. - Constance Thierry; Géry Casiez; Jean-Christophe Dubois; Yolande Le Gall; Sylvain Malacria; Thomas Pietrzak; Arnaud Martin 001; Pierrick Uro (IHM, 2024)

Evidential uncertainty sampling strategies for active learning. - Arthur Hoarau; Vincent Lemaire 001; Yolande Le Gall; Jean-Christophe Dubois; Arnaud Martin 001 (Mach. Learn., 2024)