Recommendation ITU-T F.748.13 (06/2021) Technical framework for a shared machine learning system
Summary
History
FOREWORD
Table of Contents
1 Scope
2 References
3 Definitions
     3.1 Terms defined elsewhere
     3.2 Terms defined in this Recommendation
4 Abbreviations and acronyms
5 Conventions
6 Overview of the shared machine learning system
7 Roles in the shared machine learning system
     7.1 Overview
     7.2 Data provider
     7.3 Computation platform
     7.4 Result receiver
     7.5 Task initiator
8 Technical requirements of the shared machine learning system
     8.1 Basic functional requirements
          8.1.1 Data management functional requirements
          8.1.2 Algorithm management functional requirements
          8.1.3 Computation management functional requirements
     8.2 Scalability requirements
     8.3 Reliability requirements
     8.4 Compatibility requirements
     8.5 Performance requirements
     8.6 Usability requirements
9 Security requirements of the shared machine learning system
     9.1 Authentication requirements
     9.2 Access control requirements
     9.3 Security auditing requirements
     9.4 Data security requirements
     9.5 Privacy protection requirements
10 Technical architecture, functional components, and processing procedure of the shared machine learning system in centralized mode
     10.1 Technical architecture of the shared machine learning system in the centralized mode
     10.2 Functional components of the shared machine learning system in the centralized mode
     10.3 Processing procedures of the shared machine learning system in the centralized mode
11 Technical architecture, functional components, and processing procedure of the shared machine learning system in decentralized mode
     11.1 Technical architecture of the shared machine learning system in the decentralized mode
     11.2 Functional components of the shared machine learning system in the decentralized mode
     11.3 Processing procedures of the shared machine learning system in the decentralized mode
Appendix I  Use cases for shared machine learning systems
     I.1 Use case: Improving modules for recognizing telecom frauds using data from multiple networks
     I.2 Intelligent credit and risk control use case
     I.3 Intelligent marketing use case
Bibliography
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