Benjamin Quost

Orcid: 0000-0002-0456-9953

According to our database1, Benjamin Quost authored at least 39 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Soft Learning Probabilistic Circuits.
CoRR, 2024

Probabilistic Circuits with Constraints via Convex Optimization.
CoRR, 2024

2023
Cautious weighted random forests.
Expert Syst. Appl., 2023

Robust Consumption Planning from Uncertain Power Demand Predictions.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

Learning calibrated belief functions from conformal predictions.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

Cautious Decision-Making for Tree Ensembles.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2023

Self Learning using Venn-Abers predictors.
Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023

2022
Forêts aléatoires prudentes : une nouvelle stratégie de décision et quelques expériences.
Proceedings of the Rencontres francophones sur la Logique Floue et ses Applications, 2022

Explications contrefactuelles pour les forêts aléatoires prudentes.
Proceedings of the Rencontres francophones sur la Logique Floue et ses Applications, 2022

Vehicle consumption estimation via calibrated Gaussian Process regression.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

A Robust Bayesian Estimation Approach for the Imprecise Plackett-Luce Model.
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.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

Decision-making from Partial Instances by Active Feature Querying.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

2020
Cautious relational clustering: A thresholding approach.
Expert Syst. Appl., 2020

Dealing with Atypical Instances in Evidential Decision-Making.
Proceedings of the Scalable Uncertainty Management - 14th International Conference, 2020

Inferring from an Imprecise Plackett-Luce Model: Application to Label Ranking.
Proceedings of the Scalable Uncertainty Management - 14th International Conference, 2020

2018
Classification by pairwise coupling of imprecise probabilities.
Pattern Recognit., 2018

2017
Moving object detection and segmentation in urban environments from a moving platform.
Image Vis. Comput., 2017

Parametric classification with soft labels using the evidential EM algorithm: linear discriminant analysis versus logistic regression.
Adv. Data Anal. Classif., 2017

2016
Clustering and classification of fuzzy data using the fuzzy EM algorithm.
Fuzzy Sets Syst., 2016

2015
Estimating energy consumption of a PHEV using vehicle and on-board navigation data.
Proceedings of the 2015 IEEE Intelligent Vehicles Symposium, 2015

2014
CEVCLUS: evidential clustering with instance-level constraints for relational data.
Soft Comput., 2014

Editorial.
Int. J. Approx. Reason., 2014

On modeling ego-motion uncertainty for moving object detection from a mobile platform.
Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

Soft label based semi-supervised boosting for classification and object recognition.
Proceedings of the 13th International Conference on Control Automation Robotics & Vision, 2014

Logistic Regression of Soft Labeled Instances via the Evidential EM Algorithm.
Proceedings of the Belief Functions: Theory and Applications, 2014

2013
Sound Source Localization from Uncertain Information Using the Evidential EM Algorithm.
Proceedings of the Scalable Uncertainty Management - 7th International Conference, 2013

2012
CECM: Constrained evidential C-means algorithm.
Comput. Stat. Data Anal., 2012

Correcting Binary Imprecise Classifiers: Local vs Global Approach.
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.
Int. J. Approx. Reason., 2011

Combining Binary Classifiers with Imprecise Probabilities.
Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2011

CEVCLUS: Constrained evidential clustering of proximity data.
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology, 2011

2010
Clustering Fuzzy Data Using the Fuzzy EM Algorithm.
Proceedings of the Scalable Uncertainty Management - 4th International Conference, 2010

CECM: Adding pairwise constraints to evidential clustering.
Proceedings of the FUZZ-IEEE 2010, 2010

2009
Learning from data with uncertain labels by boosting credal classifiers.
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.
Inf. Fusion, 2008

Refined classifier combination using belief functions.
Proceedings of the 11th International Conference on Information Fusion, 2008

2007
Pairwise classifier combination using belief functions.
Pattern Recognit. Lett., 2007

2005
Contextual Discounting of Belief Functions.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2005


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