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Shuyin Xia

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Aug 2026

Multi-Granularity Graph Contrastive Learning Framework via Granular-Ball on Heterogeneous Graphs.

Graph Contrastive Learning (GCL) is a popular self-supervised learning (SSL) technique. However, mainstream GCL methods usually favor single fine-grained random augmentation schemes, which will destroy the structural integrity of the graph, and they largely ignore the topology of the graph structure, that is, multi-gra...

Shuyin Xia, Guan Wang, Cheng Tan et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Global to Local: Topology-Preserving Adaptive Graph Pooling via Granular-Ball

Graph pooling aims to compress the graph, including both node embeddings and their underlying topological patterns, into a more compact representation. Previous works focus primarily on the overly fine-grained representation of nodes, progressively coarsening the graph by removing nodes or merging them into clusters, t...

Sen Zhao, Gao-Jie Xu, Shuyin Xia et al. · 0 citations
Preprint Aug 2026

Adaptive $k$ Nearest Neighbors Classifier via Granular Ball Computing

Experimental results demonstrate that the proposed adaptive and efficient KNN approach via granular-ball computing outperforms existing KNN variants across multiple datasets in terms of both accuracy and efficiency.

Xiao-Yu Lian, Shu-Yin Xia, Hongxuan He et al. · 0 citations

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