19 citations · 71 across the 6 of their papers we have counts for
5 papers · 1 filter
Attention Regularized Laplace Graph for Domain Adaptation
Lingkun Luo, Liming Chen, Shiqiang Hu
In leveraging manifold learning in domain adaptation (DA), graph embedding-based DA methods have shown their effectiveness in preserving data manifold through the Laplace graph. Ho…
Discriminative Noise Robust Sparse Orthogonal Label Regression-based Domain Adaptation
Lingkun Luo, Liming Chen, Shiqiang Hu
Domain adaptation (DA) aims to enable a learning model trained from a source domain to generalize well on a target domain, despite the mismatch of data distributions between the tw…
Discriminative Label Consistent Domain Adaptation
Lingkun Luo, Liming Chen, Ying lu +1
Domain adaptation (DA) is transfer learning which aims to learn an effective predictor on target data from source data despite data distribution mismatch between source and target.…
Discriminative and Geometry Aware Unsupervised Domain Adaptation
Lingkun Luo, Liming Chen, Shiqiang Hu +2
Domain adaptation (DA) aims to generalize a learning model across training and testing data despite the mismatch of their data distributions. In light of a theoretical estimation o…
Robust Data Geometric Structure Aligned Close yet Discriminative Domain Adaptation
Lingkun Luo, Xiaofang Wang, Shiqiang Hu +1
Domain adaptation (DA) is transfer learning which aims to leverage labeled data in a related source domain to achieve informed knowledge transfer and help the classification of unl…