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View article: Unified Domain Adaptation with Discriminative Features and Similarity Preservation
Unified Domain Adaptation with Discriminative Features and Similarity Preservation Open
In visual domain adaptation, the goal is to train effective classifiers for the target domain by leveraging information from the source domain. In unsupervised domain adaptation, the source domain provides labeled data while the target dom…
View article: RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation Through Optimal Transport for Image Classification
RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation Through Optimal Transport for Image Classification Open
In traditional machine learning, the training and testing data are assumed to come from the same independent and identical distributions. This assumption, however, does not hold up in real-world applications, as differences between the tra…