From learning to meta-learning: Reduced training overhead and complexity for communication systems

Authors: Osvaldo Simeone, Sangwoo Park, Joonhyuk Kang

Conference: 2020 2nd 6G Wireless Summit (6G SUMMIT)

Abstract: We emphasise usefulness of meta-learning for communication systems to save communication resources. In this summit, we organize the reason why we believe meta-learning would be the key ingredient for future (6G) communication systems.

Fig. 4: Overall description of meta-learning. Based on data from multiple meta-training tasks (left part), inductive bias, or model class, is determined and applied to train a new meta-test task (right part).