PRIVACY AND TRUST REDEFINED IN FEDERATED MACHINE LEARNING

Privacy and Trust Redefined in Federated Machine Learning

A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures.In situations with highly sensitive data such as healthcare records, accessing this information is challenging and often prohibited.Luckily, privacy-preserving technologies have been developed to overcome this hurdle by distributing

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Education in ideological perspective

The purpose of the research is to reflect on education in the perspective of ideology, which is an analysis of the contrast between realism and idealism; This research is an analytical-inferential method and in the form of a qualitative research, after explaining and explaining the ideology, the challenges of education in the present era were inves

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