3 papers
cs.LG2026
Efficient and Scalable Granular-ball Graph Coarsening Method for Large-scale Graph Node Classification
Guan Wang, Shuyin Xia, Lei Qian +4
Graph Convolutional Network (GCN) is a model that can effectively handle graph data tasks and has been successfully applied. However, for large-scale graph datasets, GCN still face…
cs.CV2026
Square Superpixel Generation and Representation Learning via Granular Ball Computing
Shuyin Xia, Meng Yang, Dawei Dai +6
Superpixels provide a compact region-based representation that preserves object boundaries and local structures, and have therefore been widely used in a variety of vision tasks to…
cs.LG2026
Robust Smart Contract Vulnerability Detection via Contrastive Learning-Enhanced Granular-ball Training
Zeli Wang, Qingxuan Yang, Shuyin Xia +3
Deep neural networks (DNNs) have emerged as a prominent approach for detecting smart contract vulnerabilities, driven by the growing contract datasets and advanced deep learning te…