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Unsupervised domain adaptation by learning using privileged information
The latter is often violated in high-dimensional applications such as image classification which, despite this challenge, continues to serve as inspiration and benchmark for algorithm development.
Multi-Label Image Classification
Unsupervised Domain Adaptation
Practicality of generalization guarantees for unsupervised domain adaptation with neural networks
We find that all bounds are vacuous and that sample generalization terms account for much of the observed looseness, especially when these terms interact with measures of domain shift.
