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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 101–110 of 208 papers

TitleStatusHype
Node-level Contrastive Unlearning on Graph Neural Networks—0
One-step Bipartite Graph Cut: A Normalized Formulation and Its Application to Scalable Subspace Clustering—0
On Hash-Based Work Distribution Methods for Parallel Best-First Search—0
On the definition of Shape Parts: a Dominant Sets Approach—0
Optimizing embedding-related quantum annealing parameters for reducing hardware bias—0
Orientation Robust Text Line Detection in Natural Images—0
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks—0
Preconditioned Spectral Clustering for Stochastic Block Partition Streaming Graph Challenge—0
Proximity Preserving Binary Code using Signed Graph-Cut—0
Quantum Annealing based Power Grid Partitioning for Parallel Simulation—0
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