Zhengming Ding

Joint Adversarial Domain Adaptation

2019

Domain adaptation aims to transfer the enriched label knowledge from large amounts of source data to unlabeled target data. It has raised significant interest in multimedia analysis. Existing researches mainly focus on learning domain-wise transferable …

Generative Correlation Discovery Network for Multi-label Learning

2019

The goal of Multi-label learning is to predict multiple labels of each single instance. This is a challenging problem since the training data is limited, long-tail label distribution, and complicated label correlations. Generally, more training …

Deep Decision Tree Transfer Boosting

2019 · IUScholarWorks (Indiana University)

Instance transfer approaches consider source and target data together during the training process, and borrow examples from the source domain to augment the training data, when there is limited or no label in the target …