极小量
发表于 2025-3-25 05:28:22
Conference proceedings 2024r 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; Con
勤勉
发表于 2025-3-25 09:54:43
4.5 Thermal expansion of steel,lgorithms, and other state-of-the-art techniques. DEEM can learn from the data itself, without requiring external labels but we can incorporate prior on labels if available as proposed in NN-EVCLUS. The first results are shown on the MNIST dataset (digit recognition).
柔声地说
发表于 2025-3-25 13:48:34
https://doi.org/10.1007/978-3-540-44760-3 classification criteria. We conclude by presenting some preliminary experimental results, demonstrating the performance of the proposed models compared to commonly used probabilistic circuits across a range of classification tasks.
争议的苹果
发表于 2025-3-25 18:12:29
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companion
发表于 2025-3-25 23:40:11
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吹牛大王
发表于 2025-3-26 04:11:19
Deep Evidential Clustering of Imageslgorithms, and other state-of-the-art techniques. DEEM can learn from the data itself, without requiring external labels but we can incorporate prior on labels if available as proposed in NN-EVCLUS. The first results are shown on the MNIST dataset (digit recognition).
cathartic
发表于 2025-3-26 07:24:58
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爆米花
发表于 2025-3-26 11:52:57
An Evidence-Based Framework For Heterogeneous Electronic Health Records: A Case Study In Mortality Pzes multi-sourced encoders to address the heterogeneity in EHRs and combines the multi-sourced evidence using Dempster’s combination rule. Our framework significantly outperforms conventional EHR analysis methods, demonstrating higher effectiveness on two tabular encoders in mortality prediction.
neutrophils
发表于 2025-3-26 13:28:09
A Novel Privacy Preserving Framework for Training Dempster-Shafer Theory-Based Evidential Deep Neurats with the CIFAR10 and CIFAR100 datasets confirm that integrating SMC with FL in DS-based EDNNs preserves high classification accuracy while effectively handling unclear patterns, ensuring advanced decision-making and robust data privacy and security.
chronology
发表于 2025-3-26 18:27:41
0302-9743 nge on theoretical aspects on Machine learning; Statistical inference; Information fusion and optimization; Measures of uncertainty, conflict and distances; Continuous belief functions, logics, computation..978-3-031-67976-6978-3-031-67977-3Series ISSN 0302-9743 Series E-ISSN 1611-3349