Efficient Model Adaptation for Continual Learning at the Edge

Zachary A. Daniels, Jun Hu, Michael Lomnitz +5

Most machine learning (ML) systems assume stationary and matching data distributions during training and deployment. This is often a false assumption. When ML models are deployed o…