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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
Reformulating DOVER-Lap Label Mapping as a Graph Partitioning ProblemCode1
Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object TrackingCode1
Automatic Graph Partitioning for Very Large-scale Deep Learning—0
Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware—0
Refining a -nearest neighbor graph for a computationally efficient spectral clusteringCode0
Characterizing and comparing external measures for the assessment of cluster analysis and community detectionCode0
RANK: AI-assisted End-to-End Architecture for Detecting Persistent Attacks in Enterprise Networks—0
Distributed Training of Graph Convolutional Networks using Subgraph Approximation—0
Hypergraph Partitioning using Tensor Eigenvalue Decomposition—0
Optimizing embedding-related quantum annealing parameters for reducing hardware bias—0
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