103 citations · 167 across the 19 of their papers we have counts for
4 papers · 1 filter
Efficient Maximum Fair Clique Search over Large Networks
Qi Zhang, Rong-Hua Li, Zifan Zheng +3
Mining cohesive subgraphs in attributed graphs is an essential problem in the domain of graph data analysis. The integration of fairness considerations significantly fuels interest…
Learning to Generate Parameters of ConvNets for Unseen Image Data
Shiye Wang, Kaituo Feng, Changsheng Li +2
Typical Convolutional Neural Networks (ConvNets) depend heavily on large amounts of image data and resort to an iterative optimization algorithm (e.g., SGD or Adam) to learn networ…
DREAM: Domain-free Reverse Engineering Attributes of Black-box Model
Rongqing Li, Jiaqi Yu, Changsheng Li +3
Deep learning models are usually black boxes when deployed on machine learning platforms. Prior works have shown that the attributes (, the number of convolutional layers) of…
Shared Growth of Graph Neural Networks via Prompted Free-direction Knowledge Distillation
Kaituo Feng, Yikun Miao, Changsheng Li +2
Knowledge distillation (KD) has shown to be effective to boost the performance of graph neural networks (GNNs), where the typical objective is to distill knowledge from a deeper te…