30 citations · 60 across the 7 of their papers we have counts for
4 papers · 1 filter
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities
Chuang Liu, Yibing Zhan, Jia Wu +5
Graph neural networks have emerged as a leading architecture for many graph-level tasks, such as graph classification and graph generation. As an essential component of the archite…
A Deep Framework for Cross-Domain and Cross-System Recommendations
Feng Zhu, Yan Wang, Chaochao Chen +3
Cross-Domain Recommendation (CDR) and Cross-System Recommendations (CSR) are two of the promising solutions to address the long-standing data sparsity problem in recommender system…
Deep Active Learning for Anchor User Prediction
Anfeng Cheng, Chuan Zhou, Hong Yang +4
Predicting pairs of anchor users plays an important role in the cross-network analysis. Due to the expensive costs of labeling anchor users for training prediction models, we consi…
TLR: Transfer Latent Representation for Unsupervised Domain Adaptation
Pan Xiao, Bo Du, Jia Wu +3
Domain adaptation refers to the process of learning prediction models in a target domain by making use of data from a source domain. Many classic methods solve the domain adaptatio…