The development and application of federated machine learning are facing the critical challenges about how to balance the tradeoff among…
United States
This guide aims to establish a standardized reference framework and technical protocols for implementing large-scale artificial intelligence (AI) models in…
The standard specifies a type of compilation interface and its intermediate representation used for deep learning model computation tasks. This…
This NIST AI report develops a taxonomy of concepts and defines terminology in the field of adversarial machine learning (AML).…
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.…
This standard specifies the basic functions, performance requirements, software ecosystem, and application scenarios of the deep learning chip for the…
This guide provides data contribution measurement methods for federated machine learning. The document provides guidance with respect to data trading…
Guidance for improving the security auditability and traceability of blockchain-based federated machine Learning is provided in this document. Blockchain-based federated…
This is an adoption of the Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI)–Technical Specification Neural Network Watermarking…
ANSI/CTA 2107-A
The Use of Artificial Intelligence in Health Care: Managing, Characterizing, and Safeguarding Data
Project to update CTA 2107 clarifying existing language. To include: – Clarifying the use of the term “validation”; – Relocating…
IEEE 2941.2
IEEE Standard for Application Programming Interfaces (APIs) for Deep Learning (DL) Inference Engines
A set of application programming interfaces (APIs) that is aimed at breaking down the barriers between different deep learning (DL)…
