12 citations · 17 across the 2 of their papers we have counts for
4 papers · 1 filter
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.…
Brenier approach for optimal transportation between a quasi-discrete measure and a discrete measure
Ying Lu, Liming Chen, Alexandre Saidi +1
Correctly estimating the discrepancy between two data distributions has always been an important task in Machine Learning. Recently, Cuturi proposed the Sinkhorn distance which mak…
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…
Optimal Transport for Deep Joint Transfer Learning
Ying Lu, Liming Chen, Alexandre Saidi
Training a Deep Neural Network (DNN) from scratch requires a large amount of labeled data. For a classification task where only small amount of training data is available, a common…