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graph partitioning

Graph Partitioning is generally the first step of distributed graph computing tasks. The targets are load-balance and minimizing the communication volume.

Papers

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Showing 141–150 of 208 papers

TitleStatusHype
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution—0
Graph Neural Networks on Graph Databases—0
Graph Partitioning and Graph Neural Network based Hierarchical Graph Matching for Graph Similarity Computation—0
Graph Partitioning for Independent Sets—0
Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning—0
Graph Partitioning with Acyclicity Constraints—0
Hierarchical Clustering via Spreading Metrics—0
Higher-Order Correlation Clustering for Image Segmentation—0
Hypergraph Partitioning using Tensor Eigenvalue Decomposition—0
Improved Analysis of Spectral Algorithm for Clustering—0
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