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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 81–90 of 208 papers

TitleStatusHype
Local Motif Clustering via (Hyper)Graph PartitioningCode0
A Bayesian Approach To Graph Partitioning—0
WawPart: Workload-Aware Partitioning of Knowledge Graphs—0
Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and SimplicityCode1
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks—0
Generalized Spectral Clustering for Directed and Undirected Graphs—0
SUGAR: Efficient Subgraph-level Training via Resource-aware Graph Partitioning—0
Deep Learning and Spectral Embedding for Graph Partitioning—0
Trading Quality for Efficiency of Graph Partitioning: An Inductive Method across Graphs—0
RAMA: A Rapid Multicut Algorithm on GPUCode1
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