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Titlebook: Advanced Intelligent Computing Theories and Applications - With Aspects of Theoretical and Methodolo; Third International De-Shuang Huang,

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Causal Inference and Missing Data Problems,r of 2.,where N is the number of neurons. Besides,the case analysis and simulation tests have been carried out for the recognition of images in this paper, and the result indicates that QPDN can recognize the images or patterns effectively and its working process accords with quantum evolvement process.
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Causal Inference and Missing Data Problems,he filtered results are fed back. Therefore, the solution promises to reduce time and cost of data transfer between the front-end system and the back-end system. Finally, a prototype system, GTSys named, is implemented and verified on simulation platform.
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Causal Inference and Missing Data Problems,ransferred to other entities, if somehow spending budgets on risk control actions. Results from the proposed formulations are compared in case studies. The model attempts to apply risk based budget guidelines to risk reduction measurement with a portfolio-based risk framework.
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