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Titlebook: Knowledge Science, Engineering and Management; 17th International C Cungeng Cao,Huajun Chen,Yonghao Wang Conference proceedings 2024 The Ed

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WGGAL: A Practical Time Series Forecasting Framework for Dynamic Cloud Environmentstion (APH Loss) to constrain prediction values, effectively reducing resource underestimation while maintaining prediction accuracy and avoiding issues such as out-of-memory errors. Experimental results demonstrate that, compared to state-of-the-art forecasting methods, WGGAL reduces forecasting err
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DA-NAS: Learning Transferable Architecture for Unsupervised Domain Adaptationes into consideration, the searched architectures aim to facilitate a more effective transfer from the source domain to the target domain. The extensive experiments have validated our searched model on unsupervised domain adaptation.
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