43 citations · 50 across the 8 of their papers we have counts for
4 papers · 1 filter
Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples
Wei Duan, Junyu Xuan, Maoying Qiao +1
Graph Convolutional Neural Networks (GCNs) has been generally accepted to be an effective tool for node representations learning. An interesting way to understand GCNs is to think…
Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning
Junyu Xuan, Jie Lu, Guangquan Zhang
Transfer learning where the behavior of extracting transferable knowledge from the source domain(s) and reusing this knowledge to target domain has become a research area of great…
Open Set Domain Adaptation: Theoretical Bound and Algorithm
Zhen Fang, Jie Lu, Feng Liu +2
The aim of unsupervised domain adaptation is to leverage the knowledge in a labeled (source) domain to improve a model's learning performance with an unlabeled (target) domain -- t…
Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization
Junyu Xuan, Jie Lu, Guangquan Zhang +1
The cooperative hierarchical structure is a common and significant data structure observed in, or adopted by, many research areas, such as: text mining (author-paper-word) and mult…