Abstract
This lecture overviews Domain Adaptation that has many applications in DNN training and adaptation. It covers the following topics in detail: Domain Shift, Unsupervised Domain Adaptation (Domain-specific Whitening Transform, Min-entropy Consensus loss, Maximum Classification Discrepancy, Sliced Wasserstein Discrepancy), Deep Learning methods for Unsupervised Domain Adaptation ( DLID: Deep learning for DA by Interpolating between Domains), Semi-supervised Adaptation (Entropy minimization, minmax entropy), Supervised Domain Adaptation, Bayesian Domain Adaptation, Margin Disparity Discrepancy.
Domain Adaptation and Transfer Learning.
Domain shift.
Domain-Adaptation-v2.5.4-Summary-1