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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 71–80 of 208 papers

TitleStatusHype
AGO: Boosting Mobile AI Inference Performance by Removing Constraints on Graph Optimization—0
Sub-Graph Learning for Spatiotemporal Forecasting via Knowledge Distillation—0
Agglomeration of Polygonal Grids using Graph Neural Networks with applications to Multigrid solvers—0
Robust Fair Clustering: A Novel Fairness Attack and Defense FrameworkCode0
Fine-tuning Partition-aware Item Similarities for Efficient and Scalable RecommendationCode0
Nimble GNN Embedding with Tensor-Train Decomposition—0
Neural Improvement Heuristics for Graph Combinatorial Optimization ProblemsCode0
Learning to Solve Combinatorial Graph Partitioning Problems via Efficient ExplorationCode1
More Recent Advances in (Hyper)Graph Partitioning—0
Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and LocalizationCode2
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