Results 21 to 30 of about 105,297 (262)
Vestnik KRAUNC: Fiziko-Matematičeskie Nauki, 2021 При решении задач классификации с использование глубокого обучения сталкиваются с проблемой сходимости модели. Такая проблема возникает из за ограниченного объема данных в выборках.
Бобин, А.С.
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A Reinforcement One-Shot Active Learning Approach for Aircraft Type Recognition
IEEE Access, 2019 Target recognition is an important aspect of air traffic management, but the study on automatic aircraft identification is still in the exploratory stage.
Honglan Huang +4 more
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Entropy Theory for Cross-Sections [PDF]
Geometric and Functional Analysis, 2010 We define the notion of entropy for a cross section of an action of continuous amenable group and relate it to the entropy of the ambient action. As a result, we are able to answer a question of J.P. Thouvenot about completely positive entropy actions.
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Active function Cross-Entropy Clustering
Expert Systems with Applications, 2017 Gaussian Mixture Models (GMM) have found many applications in density estimation and data clustering. However, the model does not adapt well to curved and strongly nonlinear data. Recently there appeared an improvement called AcaGMM (Active curve axis Gaussian Mixture Model), which fits Gaussians along curves using an EM-like (Expectation Maximization)
Spurek, Przemysław +2 more
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Ricci Curvature-Based Semi-Supervised Learning on an Attributed Network
Entropy, 2021 In recent years, on the basis of drawing lessons from traditional neural network models, people have been paying more and more attention to the design of neural network architectures for processing graph structure data, which are called graph neural ...
Wei Wu, Guangmin Hu, Fucai Yu
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Journal of Uncertainty Analysis and Applications, 2015 This paper deals with the divergence of fuzzy variables from a priori one. Within the framework of credibility theory, a fuzzy cross-entropy is defined to measure the divergence, and some mathematical properties are investigated. Furthermore, a minimum cross-entropy principle is proposed, which tells us that out of all membership functions satisfying ...
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Parallel cross-entropy optimization [PDF]
2007 Winter Simulation Conference, 2007 The cross-entropy (CE) method is a modern and effective optimization method well suited to parallel implementations. There is a vast array of problems today, some of which are highly complex and can take weeks or even longer to solve using current optimization techniques.
Evans, Gareth +2 more
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IEEE Access, 2023 Well-Being analysis is an approach that integrates deterministic criteria with probabilistic methods, and it plays a crucial role in the operational planning of power systems.
Dongli Xu +3 more
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Cybernetics and Information Technologies, 2015 Due to some drawbacks of the cross entropy between Single Valued Neutrosophic Sets (SVNSs) in dealing with decision-making problems, the existing single valued neutrosophic cross entropy indicates an asymmetrical phenomenon or may produce an undefined ...
Ye Jun
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Joint Early Stopping Criterions for Protograph LDPC Codes-Based JSCC System in Images Transmission
Entropy, 2021 In this paper, a joint early stopping criterion based on cross entropy (CE), named joint CE criterion, is presented for double-protograph low-density parity-check (DP-LDPC) codes-based joint source-channel coding (JSCC) systems in images transmission to ...
Zhiping Xu, Lin Wang, Shaohua Hong
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