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 | Distributed neural tensor completion for network monitoring data recovery
However, the training process of existing methods is often time-consuming due to massive data and unreasonable network resource allocation. Thus motivated, we propose a distributed neural tensor completion method, named D-NORM, which simultaneously optimizes both recovery accuracy and time.
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 | False data injection attacks data recovery in smart grids: A graph ...
False data injection (FDI) attacks, one of the most classical cyber attacks, have increasingly posed a significant threat to the security and reliability of power systems [5]. Such attacks, mislead the system state estimation results, by manipulating the measurements of sensors, and thereby affecting the secure operations of the power system [6]. Research on FDI attacks and their data recovery ...
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 | Kernel Bayesian tensor ring decomposition for multiway data recovery
With the aid of side information, the recovery performance of the methods above is improved. However, all matrix-based methods with side information encounter difficulties when dealing with high-order data because they cannot incorporate specific side information enhancements.
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