Titlebook: Integrated Uncertainty in Knowledge Modelling and Decision Making; 10th International S Katsuhiro Honda,Bac Le,Youji Kohda Conference proce

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书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making影响因子(影响力)




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making影响因子(影响力)学科排名




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making网络公开度




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making网络公开度学科排名




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making被引频次




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making被引频次学科排名




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making年度引用




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making年度引用学科排名




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making读者反馈




书目名称Integrated Uncertainty in Knowledge Modelling and Decision Making读者反馈学科排名

强制性

干旱

Joint Multiple Efficient Neighbors and Graph Learning for Multi-view Clusteringng sparsity and connectivity simultaneously is challenging. Multi-view clustering (MC) integrates complementary information from different views. However, most existing methods introduce noise or ignore relevant data structures. This paper introduces a Joint multiple efficient neighbors and Graph (J

avulsion

Maximum-Margin Nearest Prototype Classifiers with the Sum-over-Others Loss Function and a Performanch is a weighted sum of the inverted margin and a loss function. It is reduced a difference-of-convex optimization problem, and solved using the convex-concave procedure. In our latest study, to overcome limitations of the previous model, we have revised the model in both of the optimization problem

EXCEL

惰性气体

Harrowing

TouriER: Temporal Knowledge Graph Completion by Leveraging Fourier Transformsporal information, it poses a complex problem with larger data size, increased complexity in interactions between objects, and a potential for information overlap across time intervals. In this research, we introduce a novel model called TouriER, based on the MetaFormer architecture, to learn tempor

BOAST

Machine Learned KPI Goal Preferences for Explainable AI based Production Sequencinglgorithm for optimization of real-world production sequences. It is also shown how such algorithms can be both parameterized and reparametrized in an explainable ad-hoc and post-hoc manner. The explanations are also used to manage contradictory and counterfactual optimization effects so that uncerta

飞镖

Unearthing Undiscovered Interests: Knowledge Enhanced Representation Aggregation for Long-Tail Recoms predominantly focus on suggesting popular items, disregarding the significance of long-tail recommendation and consequently falling short of meeting users’ personalized needs. To this end, we propose a novel approach called Knowledge-enhanced Representation Aggregation for Long-tail Recommendation

调整

A Novel Methodology for Real-Time Face Mask Detection Using PSO Optimized CNN Technique lot of precautionary measures are suggested by the World Health Organization (WHO) to prevent the spread of COVID-19, like the use of sanitizers, social distancing, and face masks. Wearing the face-masks incorrectly makes them useless and spreads the virus. In this manuscript, a convolution neural