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024	7		_a10.1007/978-3-031-67977-3 _2doi
050		4	_aQ334-342
050		4	_aTA347.A78
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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 _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
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.
650		0	_aArtificial intelligence. _958441
650		0	_aProbabilities. _965724
650	1	4	_aArtificial Intelligence. _958441
650	2	4	_aProbability Theory. _967428
700	1		_aBi, Yaxin. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _982521
700	1		_aJousselme, Anne-Laure. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _982522
700	1		_aDenoeux, Thierry. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _982523
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	_uhttps://doi.org/10.1007/978-3-031-67977-3
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