|
Y.3176
Y.3176 is an ITU-T Recommendation, building upon Y.3172 and Y.3173, specifying a framework for evaluation intelligence levels of future networks such as 5G (IMT-2020). This Recommendation provides high-level requirements and the architecture for integrating ML marketplaces in future networks including IMT-2020. Based on these requirements, the architecture for the integration of ML marketplaces is described taking into account the architectural framework in Y.3172 as a basis. Keywords architecture, federation, future networks, IMT-2020, life-cycle, machine learning, management, marketplace, model, network functions, requirements References {{Reflist External links ITU-T Recommendation Y.3176 ITU-T recommendations ITU-T Y Series Recommendations ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ITU-T
The ITU Telecommunication Standardization Sector (ITU-T) is one of the three sectors (divisions or units) of the International Telecommunication Union (ITU). It is responsible for coordinating standards for telecommunications and Information Communication Technology such as X.509 for cybersecurity, Y.3172 and Y.3173 for machine learning, and H.264/MPEG-4 AVC for video compression, between its Member States, Private Sector Members, and Academia Members. The first meeting of the World Telecommunication Standardization Assembly (WTSA), the sector's governing conference, took place on 1 March of that year. ITU-T has a permanent secretariat called the Telecommunication Standardization Bureau (TSB), which is based at the ITU headquarters in Geneva, Switzerland. The current director of the TSB is Chaesub Lee (of South Korea), whose first 4-year term commenced on 1 January 2015, and whose second 4-year term commenced on 1 January 2019. Chaesub Lee succeeded Malcolm Johnson of the Uni ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ITU-T Study Group 13
The ITU-T Study Group 13 (SG13) is a statutory group of the ITU Telecommunication Standardization Sector (ITU-T) concerned with networks, infrastructure and cloud computing, including the networking aspects of mobile telecommunications. Examples include: Y.1564, Y.1731, etc.. Recent work includes a series of standards on using machine learning in networking, such as Y.3172, Y.3173, Y.3176, and Y.3181. Administratively, SG13 is a statutory meeting of the World Telecommunication Standardization Assembly (WTSA), which creates the ITU-T Study Groups and appoints their management teams. The secretariat is provided by the Telecommunication Standardization Bureau (under Director Chaesub Lee Chaesub Lee PhD ( Korean: 이재섭) is the Director of ITU Telecommunication Standardization Bureau, the permanent secretariat of the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) and as such, an Under-Sec ...). References {{Compu-network-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ITU-T Recommendations
The ITU Telecommunication Standardization Sector (ITU-T) is one of the three sectors (divisions or units) of the International Telecommunication Union (ITU). It is responsible for coordinating standards for telecommunications and Information Communication Technology such as X.509 for cybersecurity, Y.3172 and Y.3173 for machine learning, and H.264/MPEG-4 AVC for video compression, between its Member States, Private Sector Members, and Academia Members. The first meeting of the World Telecommunication Standardization Assembly (WTSA), the sector's governing conference, took place on 1 March of that year. ITU-T has a permanent secretariat called the Telecommunication Standardization Bureau (TSB), which is based at the ITU headquarters in Geneva, Switzerland. The current director of the TSB is Chaesub Lee (of South Korea), whose first 4-year term commenced on 1 January 2015, and whose second 4-year term commenced on 1 January 2019. Chaesub Lee succeeded Malcolm Johnson of the Uni ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
