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This guide provides data contribution measurement methods for federated machine learning. The document provides guidance with respect to data trading…

The development and application of federated machine learning are facing the critical challenges about how to balance the tradeoff among…

This guide defines a machine learning framework that allows a computing task to be decomposed and distributed across edge and…

This recommended practice specifies principles, approaches, and key performance indicators for distributed training and inference of large-scale deep learning models.…

New broadcasting technologies driven by artificial intelligence (AI) are being introduced to the broadcasting workflow. These technologies are intended to…

This recommended practice provides a framework for the use of large-scale pre-trained deep learning models, including approaches, taxonomies, related roles,…

This standard establishes a comprehensive framework for mitigating security risks, privacy leaking in the development, deployment, and use of generative…