Domain Adaptation Principal Component Analysis: base linear method for learning with out-of-distribution data

1 code implementation • 28 Aug 2022 • Evgeny M Mirkes, Jonathan Bac, Aziz Fouché, Sergey V. Stasenko, Andrei Zinovyev, Alexander N. Gorban

Domain adaptation is a popular paradigm in modern machine learning which aims at tackling the problem of divergence (or shift) between the labeled training and validation datasets (source domain) and a potentially large unlabeled dataset (target domain).

Domain Adaptation