Belief Functions Theory and Applications 5th International Conference BELIEF 2018 Compiègne France September 17 21 2018 Proceedings Sébastien Destercke

An Evidential Collaborative Filtering Approach Based on Items Contents Clustering

The Belief Functions Theory for Sensors Localization in Indoor Wireless Networks

On Evidential Clustering with Partial Supervision

Exploiting Domain-Experts Knowledge Within an Evidential Process for Case Base Maintenance

The Kantorovich Problem and Wasserstein Metric in the Theory of Belief Functions

Generalised Max Entropy Classifiers

General Geometry of Belief Function Combination

Logistic Regression Revisited: Belief Function Analysis

From Relations Between Sets to Relations Between Belief Functions

Application of Belief Functions to Levee Assessment

Prejudiced Information Fusion Using Belief Functions

A Heuristic Approach for the Robust Flight Level Assignment Problem

Study of Distributed Data Fusion Using Dempster’s Rule and Cautious Operator

Uncertainty-Aware Parzen-Rosenblatt Classifier for Multiattribute Data

Birnbaum’s Importance Measure Extended for Non-coherent Systems

Evidential Independence Maximization on Twitter Network

An Evidential k-nearest Neighbors Combination Rule for Tree Species Recognition

A Compact Belief Rule-Based Classification System with Evidential Clustering

A Decomposable Entropy of Belief Functions in the Dempster-Shafer Theory

An Evidential K-Nearest Neighbor Classifier Based on Contextual Discounting and Likelihood Maximization

Measuring Market Performance with Stochastic Demand: Price of Anarchy and Price of Uncertainty

On the Conflict Measures Agreed with the Combining Rules

Linear Belief Functions for Data Analytics

Outer Approximations of Coherent Lower Probabilities Using Belief Functions

An Ordered Family of Consistency Measures of Belief Functions

Active Evidential Calibration of Binary SVM Classifiers

Decision Making: A Beliefs, Preferences and Constraints Model

Belief and Plausibility Functions on the Space of Scalar Products and Applications

E2CM: An Evolutionary Version of Evidential C-Means Clustering Algorithm

Contrasting Two Laws of Large Numbers from Possibility Theory and Imprecise Probability

Improved Performance of EK-NNClus by Selecting Appropriate Parameter

An Empirical Study to Determine the Optimal k in Ek-NNclus Method

Evidential Community Detection Based on Density Peaks