Machine learning for a 5G future: Follow Kaleidoscope 2018 online
The tenth edition of ITU’s flagship academic event opens today in Santa Fe, Argentina, bringing researchers together with standardization experts to discuss Machine Learning’s contribution to emerging 5G systems.
Kaleidoscope 2018: Machine Learning for a 5G future, 26-28 November, is hosted by the Universidad Tecnológica Nacional.
The conference features a keynote address exploring the impact of Machine Learning on 5G planning and deployment in the Americas.
Three tutorials will look at the opportunities as well as the risks attached to Artificial Intelligence; the latest pattern-recognition techniques; and ‘strong’ or ‘general’ Artificial Intelligence, the prospect of a giving a human mind to machines.
A special session – the Jules Verne Corner – will discuss the future of work and privacy in the era of Artificial Intelligence.
Presentations of academic papers are set to address:
- Quality of Experience, networking efficiency, and video streaming
- ‘5G Cognitive Autonomous Networks’
- Cloud-optimized 5G networking and automated network slicing
- Optimization of data management
- Gender dimensions of Artificial Intelligence
- Ethical considerations relevant to Machine Learning
Kaleidoscope, Machine Learning and ITU
Machine Learning is supporting the smarter use of network-generated data, enabling network operators and service providers to adapt to changes in traffic patterns, security risks and user behaviour.
The topic is gaining a larger share of the ITU standardization work programme in fields such as coding algorithms; data processing and management; and network management and orchestration.
Authors of outstanding Kaleidoscope papers will be invited to contribute to the work of the ITU Focus Group on ‘Machine Learning for Future Networks including 5G’.
Kaleidoscope events are peer-reviewed academic conferences that increase dialogue between academics and ICT standardization experts. The aim of the conference is to identify emerging trends in ICT research and associated implications for international standardization.