- Accepted by Journal of Lightwave Technology (JLT), extended from ECOC 2020.
- Proposed a meta-learning-assisted training framework for machine-learning-based physical layer models. This framework improves model robustness to agnostic uncertain parameters during offline training and enables the model to efficiently adapt to the real system with fewer data.
