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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 51–100 of 208 papers

TitleStatusHype
Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning—0
Data Clustering and Graph Partitioning via Simulated Mixing—0
Deep Affinity Net: Instance Segmentation via Affinity—0
Deep Learning and Spectral Embedding for Graph Partitioning—0
Algorithms for metric learning via contrastive embeddings—0
Higher-Order Correlation Clustering for Image Segmentation—0
Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation—0
DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks—0
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks—0
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks—0
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution—0
Distributed Compressed Sparse Row Format for Spiking Neural Network Simulation, Serialization, and Interoperability—0
Graph Neural Networks on Graph Databases—0
CATGNN: Cost-Efficient and Scalable Distributed Training for Graph Neural Networks—0
Initialization for Network Embedding: A Graph Partition Approach—0
An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training—0
Graph Partitioning and Graph Neural Network based Hierarchical Graph Matching for Graph Similarity Computation—0
Edge-set reduction to efficiently solve the graph partitioning problem with the genetic algorithm—0
Dual-Bounded Nonlinear Optimal Transport for Size Constrained Min Cut Clustering—0
A new cut-based genetic algorithm for graph partitioning applied to cell formation—0
Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning—0
Biologically-Constrained Graphs for Global Connectomics Reconstruction—0
Efficient Partitioning Method of Large-Scale Public Safety Spatio-Temporal Data based on Information Loss Constraints—0
Efficient Video Segmentation Using Parametric Graph Partitioning—0
An Incremental Reseeding Strategy for Clustering—0
_2-norm Flow Diffusion in Near-Linear Time—0
Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware—0
Engineering a direct k-way Hypergraph Partitioning Algorithm—0
Evolutionary Acyclic Graph Partitioning—0
Circuit Partitioning for Multi-Core Quantum Architectures with Deep Reinforcement Learning—0
Fair and skill-diverse student group formation via constrained k-way graph partitioning—0
Classifier Based Graph Construction for Video Segmentation—0
Fast Algorithms for Directed Graph Partitioning Using Flows and Reweighted Eigenvalues—0
FastGAS: Fast Graph-based Annotation Selection for In-Context Learning—0
Distributed Training of Large Graph Neural Networks with Variable Communication Rates—0
Combining Multiple Clusterings via Crowd Agreement Estimation and Multi-Granularity Link Analysis—0
FGPGA: An Efficient Genetic Approach for Producing Feasible Graph Partitions—0
Fine-Grained Bipartite Concept Factorization for Clustering—0
Flow-Based Algorithms for Local Graph Clustering—0
From Free Text to Clusters of Content in Health Records: An Unsupervised Graph Partitioning Approach—0
From Text to Topics in Healthcare Records: An Unsupervised Graph Partitioning Methodology—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
Generalized Spectral Clustering for Directed and Undirected Graphs—0
BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs—0
A Design Flow for Mapping Spiking Neural Networks to Many-Core Neuromorphic Hardware—0
GNNIE: GNN Inference Engine with Load-balancing and Graph-Specific Caching—0
Graph-based Topic Extraction from Vector Embeddings of Text Documents: Application to a Corpus of News Articles—0
AGO: Boosting Mobile AI Inference Performance by Removing Constraints on Graph Optimization—0
Distributed Training of Graph Convolutional Networks using Subgraph Approximation—0
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