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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
Higher-Order Correlation Clustering for Image Segmentation—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
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks—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
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution—0
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks—0
Graph Neural Networks on Graph Databases—0
Distributed Compressed Sparse Row Format for Spiking Neural Network Simulation, Serialization, and Interoperability—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
Distributed Training of Large Graph Neural Networks with Variable Communication Rates—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
BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs—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
A Design Flow for Mapping Spiking Neural Networks to Many-Core Neuromorphic Hardware—0
Distributed Training of Graph Convolutional Networks using Subgraph Approximation—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 Power-law Graph Computing: Theoretical and Empirical Analysis—0
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