Titlebook: Algorithms and Architectures for Parallel Processing; 21st International C Yongxuan Lai,Tian Wang,Aniello Castiglione Conference proceeding

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書(shū)目名稱Algorithms and Architectures for Parallel Processing影響因子(影響力)




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書(shū)目名稱Algorithms and Architectures for Parallel Processing網(wǎng)絡(luò)公開(kāi)度




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書(shū)目名稱Algorithms and Architectures for Parallel Processing讀者反饋




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Versorgung und soziale Absicherungthe precision, recall, and average precision of the proposed model have been improved to varying degrees. It achieves 86.2% Precision, 98.4% Recall, and 90.8% Average Precision (AP), which is 7.96, 0.45, and 0.58 points higher than R-RetinaNet.

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GlowImp: Combining GLOW and?GAN for?Multivariate Time Series Imputationdimensionality of the inputs as a way of combatting the high computational costs associated with Glow models. The result is an imputation process with state-of-the-art accuracy (ROC), as demonstrated with two public datasets.

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Error Serial Episodes Discovery from Mobile Payment Log in Distributed ETCperiments indicate that this method obtains a significant rule that . will cause the error event to occur. This rule, which is found in actual scenarios, will provide a basis for data analysis of the log, and it has been recognized by business experts from relevant institutions.

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,1. Teil Die GmbH im überblick,of data blocks. This work studies how to address the cache invalidation problem. We propose a two-phase parallel prefetching approach, which can effectively improve the cache invalidation when the compaction occurs. Our experimental results show our method can effectively improve read performance.