246 citations · 320 across the 2 of their papers we have counts for
2 papers
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★ 246 cited
Domain-Adversarial Neural Networks
Hana Ajakan, Pascal Germain, Hugo Larochelle +2
We introduce a new representation learning algorithm suited to the context of domain adaptation, in which data at training and test time come from similar but different distributio…