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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 11–20 of 208 papers

TitleStatusHype
Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and SimplicityCode1
RAMA: A Rapid Multicut Algorithm on GPUCode1
Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural NetworksCode1
Reformulating DOVER-Lap Label Mapping as a Graph Partitioning ProblemCode1
Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object TrackingCode1
Accurate and versatile 3D segmentation of plant tissues at cellular resolutionCode1
Graph Neural Network Based Coarse-Grained Mapping PredictionCode1
Generalized Spectral Clustering via Gromov-Wasserstein LearningCode1
PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed TrainingCode0
Demystifying Distributed Training of Graph Neural Networks for Link PredictionCode0
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