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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 51–75 of 208 papers

TitleStatusHype
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks—0
BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs—0
Efficient Partitioning Method of Large-Scale Public Safety Spatio-Temporal Data based on Information Loss Constraints—0
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate CommunicationCode1
Creating Multi-Level Skill Hierarchies in Reinforcement LearningCode0
Fast Algorithms for Directed Graph Partitioning Using Flows and Reweighted Eigenvalues—0
One-step Bipartite Graph Cut: A Normalized Formulation and Its Application to Scalable Subspace Clustering—0
Distributed Compressed Sparse Row Format for Spiking Neural Network Simulation, Serialization, and Interoperability—0
Inductive Graph UnlearningCode0
Distributed Graph Embedding with Information-Oriented Random WalksCode0
A parameter-free graph reduction for spectral clustering and SpectralNetCode0
Random projection tree similarity metric for SpectralNetCode0
Random Projection Forest Initialization for Graph Convolutional NetworksCode0
Approximate spectral clustering with eigenvector selection and self-tuned kCode0
Approximate spectral clustering density-based similarity for noisy datasetsCode0
Refining a k-nearest neighbor graph for a computationally efficient spectral clusteringCode0
Graph Construction using Principal Axis Trees for Simple Graph ConvolutionCode0
Fair and skill-diverse student group formation via constrained k-way graph partitioning—0
Task-specific Scene Structure RepresentationsCode1
Scalable Graph Convolutional Network Training on Distributed-Memory Systems—0
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
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