Wildly Unsupervised Domain Adaptation
1 papers with code • 4 benchmarks • 1 datasets
Transferring knowledge from a noisy source domain to unlabeled target domain.
Most implemented papers
Butterfly: One-step Approach towards Wildly Unsupervised Domain Adaptation
Hence, we consider a new, more realistic and more challenging problem setting, where classifiers have to be trained with noisy labeled data from SD and unlabeled data from TD -- we name it wildly UDA (WUDA).