Joint discriminative subspace and distribution adaptation for unsupervised domain adaptation
E Gholenji, J Tahmoresnezhad - Applied Intelligence, 2020 - Springer
In traditional machine learning algorithms, the classification models are learned on the
training data (source domain) to reuse for labelling the test data (target domain) where the …
training data (source domain) to reuse for labelling the test data (target domain) where the …
Joint discriminative subspace and distribution adaptation for unsupervised domain adaptation
E Gholenji, J Tahmoresnezhad - Applied Intelligence, 2020 - dl.acm.org
In traditional machine learning algorithms, the classification models are learned on the
training data (source domain) to reuse for labelling the test data (target domain) where the …
training data (source domain) to reuse for labelling the test data (target domain) where the …
Joint discriminative subspace and distribution adaptation for unsupervised domain adaptation
G Elahe, T Jafar - Applied Intelligence, 2020 - search.proquest.com
In traditional machine learning algorithms, the classification models are learned on the
training data (source domain) to reuse for labelling the test data (target domain) where the …
training data (source domain) to reuse for labelling the test data (target domain) where the …