Benjamin Quost

Int. J. Approx. Reason., 2025

2024

Deep reinforcement learning with predictive auxiliary task for autonomous train collision avoidance.

[BibT_eX]

[DOI]

J. Rail Transp. Plan. Manag., 2024

Inferring from an imprecise Plackett-Luce model: Application to label ranking.

[BibT_eX]

[DOI]

Fuzzy Sets Syst., 2024

Soft Learning Probabilistic Circuits.

[BibT_eX]

[DOI]

Soroush Ghandi

Cassio de Campos

CoRR, 2024

Robust Discrete Bayesian Classifier Under Covariate and Label Noise.

[BibT_eX]

[DOI]

Proceedings of the Scalable Uncertainty Management - 16th International Conference, 2024

Probabilistic Circuits with Constraints via Convex Optimization.

[BibT_eX]

[DOI]

Soroush Ghandi

Cassio de Campos

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

2023

Cautious weighted random forests.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2023

Robust Consumption Planning from Uncertain Power Demand Predictions.

[BibT_eX]

[DOI]

Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

Learning calibrated belief functions from conformal predictions.

[BibT_eX]

[DOI]

Vitor Martin Bordini

Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

Cautious Decision-Making for Tree Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2023

Self Learning using Venn-Abers predictors.

[BibT_eX]

[DOI]

Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023

2022

Forêts aléatoires prudentes : une nouvelle stratégie de décision et quelques expériences.

[BibT_eX]

Proceedings of the Rencontres francophones sur la Logique Floue et ses Applications, 2022

Explications contrefactuelles pour les forêts aléatoires prudentes.

[BibT_eX]

Proceedings of the Rencontres francophones sur la Logique Floue et ses Applications, 2022

Vehicle consumption estimation via calibrated Gaussian Process regression.

[BibT_eX]

[DOI]

Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

A Robust Bayesian Estimation Approach for the Imprecise Plackett-Luce Model.

[BibT_eX]

[DOI]

Tathagata Basu

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2022

2021

Cautious Random Forests: a New Decision Strategy and some Experiments.

[BibT_eX]

[DOI]

Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

Decision-making from Partial Instances by Active Feature Querying.

[BibT_eX]

[DOI]

Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

2020

Cautious relational clustering: A thresholding approach.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2020

Dealing with Atypical Instances in Evidential Decision-Making.

[BibT_eX]

[DOI]

Proceedings of the Scalable Uncertainty Management - 14th International Conference, 2020

2018

Classification by pairwise coupling of imprecise probabilities.

[BibT_eX]

[DOI]

Pattern Recognit., 2018

2017

Moving object detection and segmentation in urban environments from a moving platform.

[BibT_eX]

[DOI]

Image Vis. Comput., 2017

Parametric classification with soft labels using the evidential EM algorithm: linear discriminant analysis versus logistic regression.

[BibT_eX]

[DOI]

Shoumei Li

Adv. Data Anal. Classif., 2017

2016

Clustering and classification of fuzzy data using the fuzzy EM algorithm.

[BibT_eX]

[DOI]

Fuzzy Sets Syst., 2016

2015

Estimating energy consumption of a PHEV using vehicle and on-board navigation data.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE Intelligent Vehicles Symposium, 2015

2014

CEVCLUS: evidential clustering with instance-level constraints for relational data.

[BibT_eX]

[DOI]

Soft Comput., 2014

Editorial.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2014

On modeling ego-motion uncertainty for moving object detection from a mobile platform.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

Soft label based semi-supervised boosting for classification and object recognition.

[BibT_eX]

[DOI]

Dingfu Zhou

Vincent Frémont

Proceedings of the 13th International Conference on Control Automation Robotics & Vision, 2014

Logistic Regression of Soft Labeled Instances via the Evidential EM Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Belief Functions: Theory and Applications, 2014

2013

Sound Source Localization from Uncertain Information Using the Evidential EM Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Scalable Uncertainty Management - 7th International Conference, 2013

2012

CECM: Constrained evidential C-means algorithm.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2012

Correcting Binary Imprecise Classifiers: Local vs Global Approach.

[BibT_eX]

[DOI]

Proceedings of the Scalable Uncertainty Management - 6th International Conference, 2012

2011

Classifier fusion in the Dempster-Shafer framework using optimized t-norm based combination rules.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2011

Combining Binary Classifiers with Imprecise Probabilities.

[BibT_eX]

[DOI]

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2011

CEVCLUS: Constrained evidential clustering of proximity data.

[BibT_eX]

[DOI]

Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology, 2011

2010

Clustering Fuzzy Data Using the Fuzzy EM Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Scalable Uncertainty Management - 4th International Conference, 2010

CECM: Adding pairwise constraints to evidential clustering.

[BibT_eX]

[DOI]

Proceedings of the FUZZ-IEEE 2010, 2010

2009

Learning from data with uncertain labels by boosting credal classifiers.

[BibT_eX]

[DOI]

Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data, 2009

2008

Refined modeling of sensor reliability in the belief function framework using contextual discounting.

[BibT_eX]

[DOI]

David Mercier

Inf. Fusion, 2008

Refined classifier combination using belief functions.

[BibT_eX]

[DOI]

Proceedings of the 11th International Conference on Information Fusion, 2008

2007

Pairwise classifier combination using belief functions.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2007

2005

Contextual Discounting of Belief Functions.

[BibT_eX]

[DOI]

David Mercier