257 citations · 270 across the 7 of their papers we have counts for
7 papers
A Global Optimization Algorithm for K-Center Clustering of One Billion Samples
Jiayang Ren, Ningning You, Kaixun Hua +2
This paper presents a practical global optimization algorithm for the K-center clustering problem, which aims to select K samples as the cluster centers to minimize the maximum wit…
Smoothness Sensor: Adaptive Smoothness-Transition Graph Convolutions for Attributed Graph Clustering
Chaojie Ji, Hongwei Chen, Ruxin Wang +2
Clustering techniques attempt to group objects with similar properties into a cluster. Clustering the nodes of an attributed graph, in which each node is associated with a set of f…
Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization
Chaojie Ji, Yijia Zheng, Ruxin Wang +2
Molecular optimization, which transforms a given input molecule X into another Y with desirable properties, is essential in molecular drug discovery. The traditional translating ap…
Boundary-aware Context Neural Network for Medical Image Segmentation
Ruxin Wang, Shuyuan Chen, Chaojie Ji +2
Medical image segmentation can provide a reliable basis for further clinical analysis and disease diagnosis. The performance of medical image segmentation has been significantly ad…
Perturb More, Trap More: Understanding Behaviors of Graph Neural Networks
Chaojie Ji, Ruxin Wang, Hongyan Wu
While graph neural networks (GNNs) have shown a great potential in various tasks on graph, the lack of transparency has hindered understanding how GNNs arrived at its predictions.…
HopGAT: Hop-aware Supervision Graph Attention Networks for Sparsely Labeled Graphs
Chaojie Ji, Ruxin Wang, Rongxiang Zhu +2
Due to the cost of labeling nodes, classifying a node in a sparsely labeled graph while maintaining the prediction accuracy deserves attention. The key point is how the algorithm l…
Cascaded Context Enhancement Network for Automatic Skin Lesion Segmentation
Ruxin Wang, Shuyuan Chen, Chaojie Ji +1
Skin lesion segmentation is an important step for automatic melanoma diagnosis. Due to the non-negligible diversity of lesions from different patients, extracting powerful context…