Pick up the PACE: Fast and Simple Domain Adaptation via Ensemble Pseudo-Labeling. (arXiv:2205.13508v1 [cs.LG])

Domain Adaptation (DA) has received widespread attention from deep learning
researchers in recent years because of its potential to improve test accuracy
with out-of-distribution labeled data. Most state-of-the-art DA algorithms
require an extensive amount of hyperparameter tuning and are computationally
intensive due to the large batch sizes required. In this work, we propose a
fast and simple DA method consisting of three stages: (1) domain alignment by
covariance matching, (2) pseudo-labeling, and (3) ensembling. We call this
method $\textbf{PACE}$, for …

arxiv domain adaptation ensemble labeling