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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 101–125 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
Graph-based Topic Extraction from Vector Embeddings of Text Documents: Application to a Corpus of News Articles—0
DistDGL: Distributed Graph Neural Network Training for Billion-Scale GraphsCode0
Accelerating Evolutionary Construction Tree Extraction via Graph Partitioning—0
Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed—0
Accurate and versatile 3D segmentation of plant tissues at cellular resolutionCode1
A Performance Guarantee for Spectral Clustering—0
Graph Neural Network Based Coarse-Grained Mapping PredictionCode1
Generalized Spectral Clustering via Gromov-Wasserstein LearningCode1
Graph Partitioning and Graph Neural Network based Hierarchical Graph Matching for Graph Similarity Computation—0
Deep Affinity Net: Instance Segmentation via Affinity—0
Regular Intersection Emptiness of Graph Problems: Finding a Needle in a Haystack of Graphs with the Help of Automata—0
Proximity Preserving Binary Code using Signed Graph-Cut—0
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation—0
Improved Analysis of Spectral Algorithm for Clustering—0
Spectral Modification of Graphs for Improved Spectral ClusteringCode0
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