Paper ID: 2211.09064
Renewing Iterative Self-labeling Domain Adaptation with Application to the Spine Motion Prediction
Gecheng Chen, Yu Zhou, Xudong Zhang, Rui Tuo
The area of transfer learning comprises supervised machine learning methods that cope with the issue when the training and testing data have different input feature spaces or distributions. In this work, we propose a novel transfer learning algorithm called Renewing Iterative Self-labeling Domain Adaptation (Re-ISDA). In this work, we propose a novel transfer learning algorithm called Renewing Iterative Self-labeling Domain Adaptation (Re-ISDA).
Submitted: Nov 14, 2022