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Ioannis Pitas (AUTH)
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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.
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