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245 1 0 _aBelief Functions: Theory and Applications
_h[electronic resource] :
_b8th International Conference, BELIEF 2024, Belfast, UK, September 2-4, 2024, Proceedings /
_cedited by Yaxin Bi, Anne-Laure Jousselme, Thierry Denoeux.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXIII, 294 p. 51 illus., 40 illus. in color.
_bonline resource.
336 _atext
_btxt
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337 _acomputer
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490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14909
505 0 _a -- Machine learning. -- Deep evidential clustering of images. -- Incremental Belief-peaks Evidential Clustering. -- Imprecise Deep Networks for Uncertain Image Classification. -- Dempster-Shafer Credal Probabilistic Circuits. -- Uncertainty quantification in regression neural networks using likelihood-based belief functions. -- An evidential time-to-event prediction model based on Gaussian random fuzzy numbers. -- Object Hallucination Detection in Large Vision Language Models via Evidential Conflict. -- Multi-oversampling with evidence fusion for imbalanced data classification. -- An Evidence-based Framework For Heterogeneous Electronic Health Records: A Case Study In Mortality Prediction. -- Conflict Management in a Distance to Prototype-Based Evidential Deep Learning. -- A Novel Privacy Preserving Framework for Training Dempster-Shafer Theory-based Evidential Deep Neural Network. -- Statistical inference. -- Large-sample theory for inferential models: A possibilistic Bernstein-von Mises theorem. -- Variational approximations of possibilistic inferential models. -- Decision theory via model-free generalized fiducial inference. -- Which statistical hypotheses are afflicted with false confidence?. -- Algebraic expression for the relative likelihood-based evidential prediction of an ordinal variable. -- Information fusion and optimization. -- Why Combining Belief Functions on Quantum Circuits?. -- SHADED: Shapley Value-based Deceptive Evidence Detection in Belief Functions. -- A Novel Optimization-Based Combination Rule for Dempster-Shafer Theory. -- Fusing independent inferential models in a black-box manner. -- Optimization under Severe Uncertainty: a Generalized Minimax Regret Approach for Problems with Linear Objectives. -- Measures of uncertainty, conflict and distances. -- A mean distance between elements of same class for rich labels. -- Threshold Functions and Operations in the Theory of Evidence. -- Mutual Information and Kullback-Leibler Divergence in the Dempster-Shafer Theory. -- An OWA-based Distance Measure for Ordered Frames of Discernment. -- Automated Hierarchical Conflict Reduction for Crowdsourced Annotation Tasks using Belief Functions. -- Continuous belief functions, logics, computation. -- Gamma Belief Functions. -- Combination of Dependent Gaussian Random Fuzzy Numbers. -- A 3-valued Logical Foundation for Evidential Reasoning. -- Accelerated Dempster Shafer using Tensor Train Representation.
520 _aThis book constitutes the refereed proceedings of the 8th International Conference on Belief Functions, BELIEF 2024, held in Belfast, UK, in September 2-4, 2024. The 30 full papers presented in this book were carefully selected and reviewed from 36 submissions. The papers cover a wide range on theoretical aspects on Machine learning; Statistical inference; Information fusion and optimization; Measures of uncertainty, conflict and distances; Continuous belief functions, logics, computation.
541 _fUABC ;
_cPerpetuidad
650 0 _aArtificial intelligence.
650 0 _aProbabilities.
650 1 4 _aArtificial Intelligence.
650 2 4 _aProbability Theory.
700 1 _aBi, Yaxin.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aJousselme, Anne-Laure.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aDenoeux, Thierry.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031679766
776 0 8 _iPrinted edition:
_z9783031679780
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14909
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-67977-3
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