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Unsupervised Domain Adaptation via Calibrating Uncertainties

Unsupervised domain adaptation (UDA) aims at inferring class labels for unlabeled target domain given a related labeled source dataset. Intuitively, a model trained on source domain normally produces higher uncertainties for unseen data... (read more)

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