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Titlebook: Belief Functions: Theory and Applications; 7th International Co Sylvie Le Hégarat-Mascle,Isabelle Bloch,Emanuel Al Conference proceedings 2

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发表于 2025-3-21 17:12:47 | 显示全部楼层 |阅读模式
期刊全称Belief Functions: Theory and Applications
期刊简称7th International Co
影响因子2023Sylvie Le Hégarat-Mascle,Isabelle Bloch,Emanuel Al
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Belief Functions: Theory and Applications; 7th International Co Sylvie Le Hégarat-Mascle,Isabelle Bloch,Emanuel Al Conference proceedings 2
影响因子This book constitutes the refereed proceedings of the 7th International Conference on Belief Functions, BELIEF 2022, held in Paris, France, in October 2022..The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion, and pattern recognition...The 29 full papers presented in this book were carefully selected and reviewed from 31 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more..
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发表于 2025-3-21 21:19:12 | 显示全部楼层
Themenmotivation und Gang der Untersuchung,at can be summarized by three numbers characterizing the most plausible predicted value, variability around this value, and epistemic uncertainty. Experiments with real datasets demonstrate the very good performance of the method as compared to state-of-the-art evidential and statistical learning algorithms.
发表于 2025-3-22 01:04:55 | 显示全部楼层
Themenmotivation und Gang der Untersuchung,assifier, which can be scaled to 48 nodes (2688 cores) at a cluster named the Texas Advanced Computing Center Frontera, with several other parallel K-NN based algorithms over 4 large datasets. Our method is able to achieve state-of-the-art scaling efficiency and accuracy on the large datasets having more than 10 million samples.
发表于 2025-3-22 05:12:21 | 显示全部楼层
Conference proceedings 2022 2022..The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine lear
发表于 2025-3-22 08:58:23 | 显示全部楼层
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An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbersat can be summarized by three numbers characterizing the most plausible predicted value, variability around this value, and epistemic uncertainty. Experiments with real datasets demonstrate the very good performance of the method as compared to state-of-the-art evidential and statistical learning algorithms.
发表于 2025-3-22 20:50:09 | 显示全部楼层
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发表于 2025-3-23 02:56:09 | 显示全部楼层
0302-9743 ubmissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more..978-3-031-17800-9978-3-031-17801-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
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