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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 151–175 of 208 papers

TitleStatusHype
A Graph-Partitioning Based Continuous Optimization Approach to Semi-supervised Clustering Problems—0
Algorithms for metric learning via contrastive embeddings—0
An Effective Branch-and-Bound Algorithm with New Bounding Methods for the Maximum s-Bundle Problem—0
A new cut-based genetic algorithm for graph partitioning applied to cell formation—0
An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training—0
An Incremental Reseeding Strategy for Clustering—0
Unsupervised Optimisation of GNNs for Node Clustering—0
A Novel Differentiable Loss Function for Unsupervised Graph Neural Networks in Graph Partitioning—0
A Performance Guarantee for Spectral Clustering—0
A Random-Key Optimizer for Combinatorial Optimization—0
Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation—0
Attribute-Enhanced Similarity Ranking for Sparse Link Prediction—0
Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning—0
Automatic Graph Partitioning for Very Large-scale Deep Learning—0
BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs—0
Biologically-Constrained Graphs for Global Connectomics Reconstruction—0
CATGNN: Cost-Efficient and Scalable Distributed Training for Graph Neural Networks—0
Circuit Partitioning for Multi-Core Quantum Architectures with Deep Reinforcement Learning—0
Classifier Based Graph Construction for Video Segmentation—0
Clustering and Community Detection with Imbalanced Clusters—0
Combining Multiple Clusterings via Crowd Agreement Estimation and Multi-Granularity Link Analysis—0
Compassionately Conservative Balanced Cuts for Image Segmentation—0
Consistency of Spectral Hypergraph Partitioning under Planted Partition Model—0
Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model—0
Content-driven, unsupervised clustering of news articles through multiscale graph partitioning—0
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