Thierry Denoeux

Orcid: 0000-0002-0660-5436

Affiliations:
  • Université de technologie de Compiègne, France


According to our database1, Thierry Denoeux authored at least 247 papers between 1993 and 2025.

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

Timeline

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Bibliography

2025
Deep evidential fusion with uncertainty quantification and reliability learning for multimodal medical image segmentation.
Inf. Fusion, 2025

2024
Combination of dependent and partially reliable Gaussian random fuzzy numbers.
Inf. Sci., 2024

Uncertainty quantification in logistic regression using random fuzzy sets and belief functions.
Int. J. Approx. Reason., 2024

Synergies between machine learning and reasoning - An introduction by the Kay R. Amel group.
Int. J. Approx. Reason., 2024

Selecting reliable instances based on evidence theory for transfer learning.
Expert Syst. Appl., 2024

r-ERBFN: An Extension of the Evidential RBFN Accounting for the Dependence Between Positive and Negative Evidence.
Proceedings of the Scalable Uncertainty Management - 16th International Conference, 2024

An Evidential Time-to-Event Prediction Model Based on Gaussian Random Fuzzy Numbers.
Proceedings of the Belief Functions: Theory and Applications, 2024

Combination of Dependent Gaussian Random Fuzzy Numbers.
Proceedings of the Belief Functions: Theory and Applications, 2024

Uncertainty Quantification in Regression Neural Networks Using Likelihood-Based Belief Functions.
Proceedings of the Belief Functions: Theory and Applications, 2024

2023
A distributional framework for evaluation, comparison and uncertainty quantification in soft clustering.
Int. J. Approx. Reason., November, 2023

Parametric families of continuous belief functions based on generalized Gaussian random fuzzy numbers.
Fuzzy Sets Syst., November, 2023

Quantifying Prediction Uncertainty in Regression Using Random Fuzzy Sets: The ENNreg Model.
IEEE Trans. Fuzzy Syst., October, 2023

A general framework for evaluating and comparing soft clusterings.
Inf. Sci., April, 2023

Reasoning with fuzzy and uncertain evidence using epistemic random fuzzy sets: General framework and practical models.
Fuzzy Sets Syst., February, 2023

Application of belief functions to medical image segmentation: A review.
Inf. Fusion, 2023

Semi-supervised multiple evidence fusion for brain tumor segmentation.
Neurocomputing, 2023

Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation.
CoRR, 2023

Belief Functions on the Real Line Defined by Transformed Gaussian Random Fuzzy Numbers.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2023

2022
Lymphoma segmentation from 3D PET-CT images using a deep evidential network.
Int. J. Approx. Reason., 2022

Belief functions and rough sets: Survey and new insights.
Int. J. Approx. Reason., 2022

Glenn Shafer - A short biography.
Int. J. Approx. Reason., 2022

Probability and statistics: Foundations and history. Special Issue in honor of Glenn Shafer.
Int. J. Approx. Reason., 2022

EGMM: An evidential version of the Gaussian mixture model for clustering.
Appl. Soft Comput., 2022

Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Stable Clustering Ensemble Based on Evidence Theory.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbers.
Proceedings of the Belief Functions: Theory and Applications, 2022

A Distributional Approach for Soft Clustering Comparison and Evaluation.
Proceedings of the Belief Functions: Theory and Applications, 2022

Trusted Multi-View Deep Learning with Opinion Aggregation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Combination of Transferable Classification With Multisource Domain Adaptation Based on Evidential Reasoning.
IEEE Trans. Neural Networks Learn. Syst., 2021

A Distributed Rough Evidential K-NN Classifier: Integrating Feature Reduction and Classification.
IEEE Trans. Fuzzy Syst., 2021

Evidence-based recommender system for high-entropy alloys.
Nat. Comput. Sci., 2021

Partial classification in the belief function framework.
Knowl. Based Syst., 2021

NN-EVCLUS: Neural network-based evidential clustering.
Inf. Sci., 2021

Distributed combination of belief functions.
Inf. Fusion, 2021

An evidential classifier based on Dempster-Shafer theory and deep learning.
Neurocomputing, 2021

A trivariate Gaussian copula stochastic frontier model with sample selection.
Int. J. Approx. Reason., 2021

Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence.
Fuzzy Sets Syst., 2021

Clustering acoustic emission data streams with sequentially appearing clusters using mixture models.
CoRR, 2021

Evidential fully convolutional network for semantic segmentation.
Appl. Intell., 2021

Deep PET/CT Fusion with Dempster-Shafer Theory for Lymphoma Segmentation.
Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Belief Function-Based Semi-Supervised Learning For Brain Tumor Segmentation.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Deep Neural Networks with Prior Evidence for Bladder Cancer Staging.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Covid-19 Classification with Deep Neural Network and Belief Functions.
Proceedings of the BIBE 2021: The Fifth International Conference on Biological Information and Biomedical Engineering, 2021

Fusion of Evidential CNN Classifiers for Image Classification.
Proceedings of the Belief Functions: Theory and Applications, 2021

Evidential Segmentation of 3D PET/CT Images.
Proceedings of the Belief Functions: Theory and Applications, 2021

2020
Calibrated model-based evidential clustering using bootstrapping.
Inf. Sci., 2020

An interval-valued utility theory for decision making with Dempster-Shafer belief functions.
Int. J. Approx. Reason., 2020

Belief functions induced by random fuzzy sets: Application to statistical inference.
CoRR, 2020

Combining clusterings in the belief function framework.
Array, 2020

Evidential Deep Neural Networks for Uncertain Data Classification.
Proceedings of the Knowledge Science, Engineering and Management, 2020

Representations of Uncertainty in AI: Beyond Probability and Possibility.
Proceedings of the A Guided Tour of Artificial Intelligence Research: Volume I: Knowledge Representation, 2020

Representations of Uncertainty in Artificial Intelligence: Probability and Possibility.
Proceedings of the A Guided Tour of Artificial Intelligence Research: Volume I: Knowledge Representation, 2020

2019
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions.
IEEE Trans. Image Process., 2019

BPEC: Belief-Peaks Evidential Clustering.
IEEE Trans. Fuzzy Syst., 2019

Logistic regression, neural networks and Dempster-Shafer theory: A new perspective.
Knowl. Based Syst., 2019

A new evidential <i>K</i>-nearest neighbor rule based on contextual discounting with partially supervised learning.
Int. J. Approx. Reason., 2019

Decision-making with belief functions: A review.
Int. J. Approx. Reason., 2019

From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group).
CoRR, 2019

Editorial: Opening up computer science.
Array, 2019

ConvNet and Dempster-Shafer Theory for Object Recognition.
Proceedings of the Scalable Uncertainty Management - 13th International Conference, 2019

Making Set-Valued Predictions in Evidential Classification: A Comparison of Different Approaches.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

An Axiomatic Utility Theory for Dempster-Shafer Belief Functions.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

Collaborative Evidential Clustering.
Proceedings of the Fuzzy Techniques: Theory and Applications, 2019

Multistep Prediction using Point-Cloud Approximation of Continuous Belief Functions.
Proceedings of the 2019 IEEE International Conference on Fuzzy Systems, 2019

Quality of Information Sources in Information Fusion.
Proceedings of the Information Quality in Information Fusion and Decision Making, 2019

2018
Quantifying Predictive Uncertainty Using Belief Functions: Different Approaches and Practical Construction.
Proceedings of the Predictive Econometrics and Big Data, 2018

Evaluating and Comparing Soft Partitions: An Approach Based on Dempster-Shafer Theory.
IEEE Trans. Fuzzy Syst., 2018

Spatial Evidential Clustering With Adaptive Distance Metric for Tumor Segmentation in FDG-PET Images.
IEEE Trans. Biomed. Eng., 2018

Evidential K-NN classification with enhanced performance via optimizing a class of parametric conjunctive t-rules.
Knowl. Based Syst., 2018

k-CEVCLUS: Constrained evidential clustering of large dissimilarity data.
Knowl. Based Syst., 2018

Identification of elastic properties in the belief function framework.
Int. J. Approx. Reason., 2018

Frequency-calibrated belief functions: Review and new insights.
Int. J. Approx. Reason., 2018

An Evidential K-Nearest Neighbor Classifier Based on Contextual Discounting and Likelihood Maximization.
Proceedings of the Belief Functions: Theory and Applications, 2018

Logistic Regression Revisited: Belief Function Analysis.
Proceedings of the Belief Functions: Theory and Applications, 2018

2017
A double-copula stochastic frontier model with dependent error components and correction for sample selection.
Int. J. Approx. Reason., 2017

Evidential grammars: A compositional approach for scene understanding. Application to multimodal street data.
Appl. Soft Comput., 2017

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

Distributed data fusion in the dempster-shafer framework.
Proceedings of the 12th System of Systems Engineering Conference, 2017

Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Accurate tumor segmentation in FDG-PET images with guidance of complementary CT images.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Constrained interval-valued linear regression model.
Proceedings of the 20th International Conference on Information Fusion, 2017

2016
A Hybrid Belief Rule-Based Classification System Based on Uncertain Training Data and Expert Knowledge.
IEEE Trans. Syst. Man Cybern. Syst., 2016

Dissimilarity Metric Learning in the Belief Function Framework.
IEEE Trans. Fuzzy Syst., 2016

Modelling and predicting partial orders from pairwise belief functions.
Soft Comput., 2016

Editing training data for multi-label classification with the k-nearest neighbor rule.
Pattern Anal. Appl., 2016

Multimodal information fusion for urban scene understanding.
Mach. Vis. Appl., 2016

Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction.
Medical Image Anal., 2016

Evidential clustering of large dissimilarity data.
Knowl. Based Syst., 2016

Evidential calibration of binary SVM classifiers.
Int. J. Approx. Reason., 2016

Prediction of future observations using belief functions: A likelihood-based approach.
Int. J. Approx. Reason., 2016

40 years of Dempster-Shafer theory.
Int. J. Approx. Reason., 2016

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

Beyond Fuzzy, Possibilistic and Rough: An Investigation of Belief Functions in Clustering.
Proceedings of the Soft Methods for Data Science, 2016

Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

Evidential Clustering: A Review.
Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2016

Joint Feature Transformation and Selection Based on Dempster-Shafer Theory.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

Identification of Elastic Properties Based on Belief Function Inference.
Proceedings of the Belief Functions: Theory and Applications, 2016

k-EVCLUS: Clustering Large Dissimilarity Data in the Belief Function Framework.
Proceedings of the Belief Functions: Theory and Applications, 2016

2015
The Classifier Chain Generalized Maximum Entropy Model for Multi-label Choice Problems.
Proceedings of the Econometrics of Risk, 2015

Estimation and Prediction Using Belief Functions: Application to Stochastic Frontier Analysis.
Proceedings of the Econometrics of Risk, 2015

An evidential classifier based on feature selection and two-step classification strategy.
Pattern Recognit., 2015

EK-NNclus: A clustering procedure based on the evidential K-nearest neighbor rule.
Knowl. Based Syst., 2015

Belief rule-based classification system: Extension of FRBCS in belief functions framework.
Inf. Sci., 2015

Interval-Valued Linear Model.
Int. J. Comput. Intell. Syst., 2015

Modeling dependence between error components of the stochastic frontier model using copula: Application to intercrop coffee production in Northern Thailand.
Int. J. Approx. Reason., 2015

Dempster-Shafer Theory Based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

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

Outcome prediction in tumour therapy based on Dempster-Shafer theory.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

Evidential multinomial logistic regression for multiclass classifier calibration.
Proceedings of the 18th International Conference on Information Fusion, 2015

Evidential Editing K-Nearest Neighbor Classifier.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

2014
Making Use of Partial Knowledge About Hidden States in HMMs: An Approach Based on Belief Functions.
IEEE Trans. Fuzzy Syst., 2014

Fusion d'informations pour la compréhension de scènes.
Traitement du Signal, 2014

Optimal Object Association in the Dempster-Shafer Framework.
IEEE Trans. Cybern., 2014

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

Fusion of multi-tracer PET images for dose painting.
Medical Image Anal., 2014

Forecasting using belief functions: An application to marketing econometrics.
Int. J. Approx. Reason., 2014

Rejoinder on "Likelihood-based belief function: Justification and some extensions to low-quality data".
Int. J. Approx. Reason., 2014

Likelihood-based belief function: Justification and some extensions to low-quality data.
Int. J. Approx. Reason., 2014

Combining statistical and expert evidence using belief functions: Application to centennial sea level estimation taking into account climate change.
Int. J. Approx. Reason., 2014

Special issue on imprecision in statistical data analysis.
Comput. Stat. Data Anal., 2014

Evidential distributed dynamic map for cooperative perception in VANets.
Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

Application of E 2 M Decision Trees to Rubber Quality Prediction.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2014

Fusion of pairwise nearest-neighbor classifiers based on pairwise-weighted distance metric and Dempster-Shafer theory.
Proceedings of the 17th International Conference on Information Fusion, 2014

Evidential combination of pedestrian detectors.
Proceedings of the British Machine Vision Conference, 2014

Evidential Logistic Regression for Binary SVM Classifier Calibration.
Proceedings of the Belief Functions: Theory and Applications, 2014

Training and Evaluating Classifiers from Evidential Data: Application to E 2 M Decision Tree Pruning.
Proceedings of the Belief Functions: Theory and Applications, 2014

The Evidence-Theoretic k-NN Rule for Rank-Ordered Data: Application to Predict an Individual's Source of Loan.
Proceedings of the Belief Functions: Theory and Applications, 2014

Predicting Stock Returns in the Capital Asset Pricing Model Using Quantile Regression and Belief Functions.
Proceedings of the Belief Functions: Theory and Applications, 2014

2013
Maximum Likelihood Estimation from Uncertain Data in the Belief Function Framework.
IEEE Trans. Knowl. Data Eng., 2013

Information Fusion on Oversegmented Images: An Application for Urban Scene Understanding.
Proceedings of the 13. IAPR International Conference on Machine Vision Applications, 2013

Evidential Grammars for Image Interpretation - Application to Multimodal Traffic Scene Understanding.
Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2013

Learning Decision Trees from Uncertain Data with an Evidential EM Approach.
Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

Optimal object association from pairwise evidential mass functions.
Proceedings of the 16th International Conference on Information Fusion, 2013

Using Dempster-Shafer theory to model uncertainty in climate change and environmental impact assessments.
Proceedings of the 16th International Conference on Information Fusion, 2013

2012
Partially supervised Independent Factor Analysis using soft labels elicited from multiple experts: application to railway track circuit diagnosis.
Soft Comput., 2012

Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints.
Pattern Anal. Appl., 2012

Relevance and truthfulness in information correction and fusion.
Int. J. Approx. Reason., 2012

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

Evidential reasoning in large partially ordered sets - Application to multi-label classification, ensemble clustering and preference aggregation.
Ann. Oper. Res., 2012

Self-stabilizing Distributed Data Fusion.
Proceedings of the Stabilization, Safety, and Security of Distributed Systems, 2012

Constructing Rule-Based Models Using the Belief Functions Framework.
Proceedings of the Advances in Computational Intelligence, 2012

Purifying training data to improve performance of multi-label classification algorithms.
Proceedings of the 15th International Conference on Information Fusion, 2012

Distributed Data Fusion for Detecting Sybil Attacks in VANETs.
Proceedings of the Belief Functions: Theory and Applications, 2012

Classification Trees Based on Belief Functions.
Proceedings of the Belief Functions: Theory and Applications, 2012

Partially-Hidden Markov Models.
Proceedings of the Belief Functions: Theory and Applications, 2012

Ranking from Pairwise Comparisons in the Belief Functions Framework.
Proceedings of the Belief Functions: Theory and Applications, 2012

Evidential Multi-label Classification Using the Random k-Label Sets Approach.
Proceedings of the Belief Functions: Theory and Applications, 2012

Conditioning in Dempster-Shafer Theory: Prediction vs. Revision.
Proceedings of the Belief Functions: Theory and Applications, 2012

Combining Statistical and Expert Evidence within the D-S Framework: Application to Hydrological Return Level Estimation.
Proceedings of the Belief Functions: Theory and Applications, 2012

2011
A Multiple-Hypothesis Map-Matching Method Suitable for Weighted and Box-Shaped State Estimation for Localization.
IEEE Trans. Intell. Transp. Syst., 2011

Classifier fusion in the Dempster-Shafer framework using optimized t-norm based combination rules.
Int. J. Approx. Reason., 2011

Ensemble clustering in the belief functions framework.
Int. J. Approx. Reason., 2011

Maximum likelihood estimation from fuzzy data using the EM algorithm.
Fuzzy Sets Syst., 2011

A Dependent Multilabel Classification Method Derived from the k-Nearest Neighbor Rule.
EURASIP J. Adv. Signal Process., 2011

Using Imprecise and Uncertain Information to Enhance the Diagnosis of a Railway Device.
Proceedings of the Nonlinear Mathematics for Uncertainty and its Applications, 2011

Semi-supervised Feature Extraction Using Independent Factor Analysis.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

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

2010
State Estimation Using Interval Analysis and Belief-Function Theory: Application to Dynamic Vehicle Localization.
IEEE Trans. Syst. Man Cybern. Part B, 2010

The Unnormalized Dempster's Rule of Combination: A New Justification from the Least Commitment Principle and Some Extensions.
J. Autom. Reason., 2010

Fault diagnosis in railway track circuits using Dempster-Shafer classifier fusion.
Eng. Appl. Artif. Intell., 2010

Representing uncertainty on set-valued variables using belief functions.
Artif. Intell., 2010

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

Statistical Inference with Belief Functions and Possibility Measures: A Discussion of Basic Assumptions.
Proceedings of the Combining Soft Computing and Statistical Methods in Data Analysis, 2010

Maximum Likelihood from Evidential Data: An Extension of the EM Algorithm.
Proceedings of the Combining Soft Computing and Statistical Methods in Data Analysis, 2010

Theory of Belief Functions for Data Analysis and Machine Learning Applications: Review and Prospects.
Proceedings of the Knowledge Science, 2010

Dempster-Shafer Reasoning in Large Partially Ordered Sets: Applications in Machine Learning.
Proceedings of the Integrated Uncertainty Management and Applications [revised papers from the International Symposium on Integrated Uncertainty Management and Applications, 2010

Evidential Multi-Label Classification Approach to Learning from Data with Imprecise Labels.
Proceedings of the Computational Intelligence for Knowledge-Based Systems Design, 2010

Fuzzy multi-label learning under veristic variables.
Proceedings of the FUZZ-IEEE 2010, 2010

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

2009
RECM: Relational evidential c-means algorithm.
Pattern Recognit. Lett., 2009

Learning from partially supervised data using mixture models and belief functions.
Pattern Recognit., 2009

Extending stochastic ordering to belief functions on the real line.
Inf. Sci., 2009

Decision fusion for postal address recognition using belief functions.
Expert Syst. Appl., 2009

An Evidence-Theoretic k-Nearest Neighbor Rule for Multi-label Classification.
Proceedings of the Scalable Uncertainty Management, Third International Conference, 2009

Multisensor data fusion for OD matrix estimation.
Proceedings of the IEEE International Conference on Systems, 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

Short-time OD matrix estimation for a complex junction using fuzzy-timed high-level petri nets.
Proceedings of the 12th International IEEE Conference on Intelligent Transportation Systems, 2009

Noiseless Independent Factor Analysis with Mixing Constraints in a Semi-supervised Framework. Application to Railway Device Fault Diagnosis.
Proceedings of the Artificial Neural Networks, 2009

A state estimation method for multiple model systems using belief function theory.
Proceedings of the 12th International Conference on Information Fusion, 2009

Fuzzy Modelling of Sensor Data for the Estimation of an Origin-Destination Matrix.
Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference, 2009

Partially-supervised learning in Independent Factor Analysis.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Belief Functions and Cluster Ensembles.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2009

2008
A <i>k</i> -Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory.
Proceedings of the Classic Works of the Dempster-Shafer Theory of Belief Functions, 2008

ECM: An evidential version of the fuzzy c.
Pattern Recognit., 2008

Refined modeling of sensor reliability in the belief function framework using contextual discounting.
Inf. Fusion, 2008

Special issue in memory of Philippe Smets (1938-2005).
Int. J. Approx. Reason., 2008

Constructing consonant belief functions from sample data using confidence sets of pignistic probabilities.
Int. J. Approx. Reason., 2008

Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence.
Artif. Intell., 2008

Mixture Model Estimation with Soft Labels.
Proceedings of the Soft Methods for Handling Variability and Imprecision, 2008

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

Map matching algorithm using belief function theory.
Proceedings of the 11th International Conference on Information Fusion, 2008

Distributed data fusion: application to confidence management in vehicular networks.
Proceedings of the 11th International Conference on Information Fusion, 2008

A New Justification of the Unnormalized Dempster's Rule of Combination from the Least Commitment Principle.
Proceedings of the Twenty-First International Florida Artificial Intelligence Research Society Conference, 2008

Multi-label classification algorithm derived from K-nearest neighbor rule with label dependencies.
Proceedings of the 2008 16th European Signal Processing Conference, 2008

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

Fusion of one-class classifiers in the belief function framework.
Proceedings of the 10th International Conference on Information Fusion, 2007

On Latent Belief Structures.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2007

Pattern Recognition and Information Fusion Using Belief Functions: Some Recent Developments.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2007

Consonant Belief Function Induced by a Confidence Set of Pignistic Probabilities.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2007

2006
Classification Using Belief Functions: Relationship Between Case-Based and Model-Based Approaches.
IEEE Trans. Syst. Man Cybern. Part B, 2006

Risk assessment based on weak information using belief functions: a case study in water treatment.
IEEE Trans. Syst. Man Cybern. Syst., 2006

Constructing belief functions from sample data using multinomial confidence regions.
Int. J. Approx. Reason., 2006

Philippe Smets (1938-2005).
Int. J. Approx. Reason., 2006

Inferring a possibility distribution from empirical data.
Fuzzy Sets Syst., 2006

In Memoriam: Philippe Smets (1938-2005).
Fuzzy Sets Syst., 2006

Fuzzy multidimensional scaling.
Comput. Stat. Data Anal., 2006

General Correction Mechanisms for Weakening or Reinforcing Belief Functions.
Proceedings of the 9th International Conference on Information Fusion, 2006

The cautious rule of combination for belief functions and some extensions.
Proceedings of the 9th International Conference on Information Fusion, 2006

Output coding of spatially dependent subclassifiers in evidential framework. Application to the diagnosis of railway track/vehicle transmission system.
Proceedings of the 9th International Conference on Information Fusion, 2006

2005
Editorial.
Int. J. Approx. Reason., 2005

Nonparametric rank-based statistics and significance tests for fuzzy data.
Fuzzy Sets Syst., 2005

R. P. Srivastava and T. J. Mock, Belief Functions in Business Decisions, in Studies in Fuzziness and Soft Computing, vol. 88, Physica-Verlag, Heidelberg (2002) ISBN 3-7908-1451-2 (345pp.)
Fuzzy Sets Syst., 2005

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

2004
EVCLUS: evidential clustering of proximity data.
IEEE Trans. Syst. Man Cybern. Part B, 2004

Principal component analysis of fuzzy data using autoassociative neural networks.
IEEE Trans. Fuzzy Syst., 2004

Clustering interval-valued proximity data using belief functions.
Pattern Recognit. Lett., 2004

Nonparametric regression analysis of uncertain and imprecise data using belief functions.
Int. J. Approx. Reason., 2004

Recycling experiments for sludge monitoring in waste water treatment.
Proceedings of the IEEE International Conference on Systems, 2004

2003
Addendum to resample and combine: an approach to improving uncertainty representation in evidential pattern classification.
Inf. Fusion, 2003

Resample and combine: an approach to improving uncertainty representation in evidential pattern classification.
Inf. Fusion, 2003

A new approach to assess risk in water treatment using the belief function framework.
Proceedings of the IEEE International Conference on Systems, 2003

Risk Assessment in Drinking Water Production Using Belief Functions.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2003

2002
Approximating the combination of belief functions using the fast Mo"bius transform in a coarsened frame.
Int. J. Approx. Reason., 2002

Multidimensional scaling of fuzzy dissimilarity data.
Fuzzy Sets Syst., 2002

2001
Inner and Outer Approximation of Belief Structures Using a Hierarchical Clustering Approach.
Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2001

A neural network-based software sensor for coagulation control in a water treatment plant.
Intell. Data Anal., 2001

Handling possibilistic labels in pattern classification using evidential reasoning.
Fuzzy Sets Syst., 2001

Likelihood-based Vs Distance-based Evidential Classifiers.
Proceedings of the 10th IEEE International Conference on Fuzzy Systems, 2001

Coarsening Approximations of Belief Functions.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2001

2000
A neural network classifier based on Dempster-Shafer theory.
IEEE Trans. Syst. Man Cybern. Part A, 2000

Multidimensional scaling of interval-valued dissimilarity data.
Pattern Recognit. Lett., 2000

Modeling vague beliefs using fuzzy-valued belief structures.
Fuzzy Sets Syst., 2000

Induction of decision trees from partially classified data using belief functions.
Proceedings of the IEEE International Conference on Systems, 2000

1999
Reasoning with imprecise belief structures.
Int. J. Approx. Reason., 1999

An hybrid neural network based system for optimization of coagulant dosing in a water treatment plant.
Proceedings of the International Joint Conference Neural Networks, 1999

State Recognition in Discrete Dynamical Systems Using Petri Nets and Evidence Theory.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1999

Handling Different Forms of Uncertainty in Regression Analysis: A Fuzzy Belief Structure Approach.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1999

1998
An evidence-theoretic k-NN rule with parameter optimization.
IEEE Trans. Syst. Man Cybern. Part C, 1998

1997
Analysis of evidence-theoretic decision rules for pattern classification.
Pattern Recognit., 1997

Function approximation in the framework of evidence theory: a connectionist approach.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

1996
Training MLPs layer by layer using an objective function for internal representations.
Neural Networks, 1996

1995
A k-nearest neighbor classification rule based on Dempster-Shafer theory.
IEEE Trans. Syst. Man Cybern., 1995

Analysis of Rainfall Forecasting using Neural Networks.
Neural Comput. Appl., 1995

Comparison of dynamic feature map models for environmental monitoring.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

Performance analysis of a MLP weight initialization algorithm.
Proceedings of the 3rd European Symposium on Artificial Neural Networks, 1995

An Adaptive k-NN Rule Based on Dempster-Shafer Theory.
Proceedings of the Computer Analysis of Images and Patterns, 6th International Conference, 1995

1993
Initializing back propagation networks with prototypes.
Neural Networks, 1993


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