Aveen Dayal*

Improving Unsupervised Domain Adaptation: A Pseudo-Candidate Set Approach

"Unsupervised domain adaptation (UDA) is a critical challenge in machine learning, aiming to transfer knowledge from a labeled source domain to an unlabeled target domain. In this work, we aim to improve target set accuracy in any existing UDA method by introducing an approach that utilizes pseudo-c…