Communication network

Machine learning systems can benefit from transfer learning of knowledge in training new models. Cognitive Autonomous Network OAM systems may utilise machine learning (ML) elements such as neural networks. MLTL producers create/possess knowledge (e.g. statistics or pre-trained models) and they may p...

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Hauptverfasser:	Stephen Mwanje, Abdelrahman Abdelkader
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY PHYSICS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
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creator	Stephen Mwanje Abdelrahman Abdelkader
description	Machine learning systems can benefit from transfer learning of knowledge in training new models. Cognitive Autonomous Network OAM systems may utilise machine learning (ML) elements such as neural networks. MLTL producers create/possess knowledge (e.g. statistics or pre-trained models) and they may publish (0) the knowledge or information about it (e.g. task, domain, context descriptions) to repositories. MLTL consumers and/or recipients can discover (1) information about knowledge by requesting reports from producers and/or repositories. The MLTL consumers/recipients may also request all/part of the actual knowledge (2) in order to use it in transfer learning (TL).
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subjects	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY PHYSICS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
title	Communication network
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