101 citations · 292 across the 21 of their papers we have counts for
37 papers
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation
Zhanke Zhou, Chenyu Zhou, Xuan Li +3
Although powerful graph neural networks (GNNs) have boosted numerous real-world applications, the potential privacy risk is still underexplored. To close this gap, we perform the f…
Enhancing Intra-class Information Extraction for Heterophilous Graphs: One Neural Architecture Search Approach
Lanning Wei, Zhiqiang He, Huan Zhao +1
In recent years, Graph Neural Networks (GNNs) have been popular in graph representation learning which assumes the homophily property, i.e., the connected nodes have the same label…
Search to Pass Messages for Temporal Knowledge Graph Completion
Zhen Wang, Haotong Du, Quanming Yao +1
Completing missing facts is a fundamental task for temporal knowledge graphs (TKGs). Recently, graph neural network (GNN) based methods, which can simultaneously explore topologica…
Searching a High-Performance Feature Extractor for Text Recognition Network
Hui Zhang, Quanming Yao, James T. Kwok +1
Feature extractor plays a critical role in text recognition (TR), but customizing its architecture is relatively less explored due to expensive manual tweaking. In this work, inspi…
Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization
Quanming Yao, Yaqing Wang, Bo Han +1
Nonconvex regularization has been popularly used in low-rank matrix learning. However, extending it for low-rank tensor learning is still computationally expensive. To address this…
KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learning
Yongqi Zhang, Zhanke Zhou, Quanming Yao +1
While hyper-parameters (HPs) are important for knowledge graph (KG) learning, existing methods fail to search them efficiently. To solve this problem, we first analyze the properti…