3.1k citations · 8.3k across the 43 of their papers we have counts for
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stat.ML2015★ 74 cited
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan +5
We introduce a new representation learning approach for domain adaptation, in which data at training and test time come from similar but different distributions. Our approach is di…
stat.ML2014★ 2.6k cited
Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin, Victor Lempitsky
Top-performing deep architectures are trained on massive amounts of labeled data. In the absence of labeled data for a certain task, domain adaptation often provides an attractive…