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Privacy-preserving computing aims to protect the personal information of users while capitalizing on the possibilities unlocked by big data. This practical introduction for students, researchers, and industry practitioners is the first cohesive and systematic...
Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the...
Transfer learning deals with how systems can quickly adapt themselves to new situations, tasks and environments. It gives machine learning systems the ability to leverage auxiliary data and models to help solve target problems when there is only a small amount of data...
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