187 citations · 1.2k across the 72 of their papers we have counts for
6 papers · 1 filter
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
Qi Zhu, Carl Yang, Yidan Xu +3
Graph neural networks (GNNs) have achieved superior performance in various applications, but training dedicated GNNs can be costly for large-scale graphs. Some recent work started…
Unsupervised Differentiable Multi-aspect Network Embedding
Chanyoung Park, Carl Yang, Qi Zhu +3
Network embedding is an influential graph mining technique for representing nodes in a graph as distributed vectors. However, the majority of network embedding methods focus on lea…
GCN for HIN via Implicit Utilization of Attention and Meta-paths
Di Jin, Zhizhi Yu, Dongxiao He +3
Heterogeneous information network (HIN) embedding, aiming to map the structure and semantic information in a HIN to distributed representations, has drawn considerable research att…
Secure Deep Graph Generation with Link Differential Privacy
Carl Yang, Haonan Wang, Ke Zhang +2
Many data mining and analytical tasks rely on the abstraction of networks (graphs) to summarize relational structures among individuals (nodes). Since relational data are often sen…
Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark
Carl Yang, Yuxin Xiao, Yu Zhang +2
Since real-world objects and their interactions are often multi-modal and multi-typed, heterogeneous networks have been widely used as a more powerful, realistic, and generic super…
cube2net: Efficient Query-Specific Network Construction with Data Cube Organization
Carl Yang, Mengxiong Liu, Frank He +2
Networks are widely used to model objects with interactions and have enabled various downstream applications. However, in the real world, network mining is often done on particular…