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Titlebook: Computational Data and Social Networks; 10th International C David Mohaisen,Ruoming Jin Conference proceedings 2021 Springer Nature Switzer

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A. S. Eddington M. A., L.L.D., D.SC., F.R.S.s to mislead the target DNNs and deceive their combined interpretation models. We evaluate the proposed attacks against two DNN model architectures coupled with four representatives of different categories of interpretation models. The experimental results demonstrate our attacks’ effectiveness in deceiving the DNN models and their interpreters.
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Differentially Private Submodular Maximization over Integer Latticen problem over the integer lattice. Our main contributions are to present differentially private approximation algorithms for both DR-submodular and integer submodular function maximization problems under cardinality constraints and analyze the sensitivity of our algorithms.
26#
發(fā)表于 2025-3-26 02:01:55 | 只看該作者
A Framework for Accelerating Graph Convolutional Networks on Massive Datasetss that we refer to as GraphSage++, ClusterGCN++, and GraphSaint++. Using graphs with order of 100 million edges, we demonstrate that we reduce the overall training time by up?to 30%, while not having a noticeable reduction in F1 scores in most cases.
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0302-9743 which was held online during November 15-17, 2021. The conference was initially planned to take place in Montreal, Quebec, Canada, but changed to an online event due to the COVID-19 pandemic.?.The 24 full and 8 short papers included in this book were carefully reviewed and selected from 57 submissio
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