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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 101–150 of 208 papers

TitleStatusHype
Reinforcement learning for instance segmentation with high-level priors—0
GNNIE: GNN Inference Engine with Load-balancing and Graph-Specific Caching—0
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution—0
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks—0
Learning Spatial Context with Graph Neural Network for Multi-Person Pose GroupingCode0
Automatic Graph Partitioning for Very Large-scale Deep Learning—0
Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware—0
Refining a -nearest neighbor graph for a computationally efficient spectral clusteringCode0
Characterizing and comparing external measures for the assessment of cluster analysis and community detectionCode0
RANK: AI-assisted End-to-End Architecture for Detecting Persistent Attacks in Enterprise Networks—0
Distributed Training of Graph Convolutional Networks using Subgraph Approximation—0
Hypergraph Partitioning using Tensor Eigenvalue Decomposition—0
Optimizing embedding-related quantum annealing parameters for reducing hardware bias—0
Graph-based Topic Extraction from Vector Embeddings of Text Documents: Application to a Corpus of News Articles—0
DistDGL: Distributed Graph Neural Network Training for Billion-Scale GraphsCode0
Accelerating Evolutionary Construction Tree Extraction via Graph Partitioning—0
Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed—0
A Performance Guarantee for Spectral Clustering—0
Graph Partitioning and Graph Neural Network based Hierarchical Graph Matching for Graph Similarity Computation—0
Deep Affinity Net: Instance Segmentation via Affinity—0
Regular Intersection Emptiness of Graph Problems: Finding a Needle in a Haystack of Graphs with the Help of Automata—0
Proximity Preserving Binary Code using Signed Graph-Cut—0
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation—0
Improved Analysis of Spectral Algorithm for Clustering—0
Spectral Modification of Graphs for Improved Spectral ClusteringCode0
Correlation clustering with local objectives—0
Weighted Laplacian and Its Theoretical Applications—0
Generalizable Resource Allocation in Stream Processing via Deep Reinforcement LearningCode0
Graph-Partitioning-Based Diffusion Convolutional Recurrent Neural Network for Large-Scale Traffic ForecastingCode0
Initialization for Network Embedding: A Graph Partition Approach—0
A 3D Convolutional Approach to Spectral Object Segmentation in Space and TimeCode0
Graph Embeddings at Scale—0
GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation—0
Biologically-Constrained Graphs for Global Connectomics Reconstruction—0
Leveraging Domain Knowledge to Improve Microscopy Image Segmentation with Lifted MulticutsCode0
Scalable Gromov-Wasserstein Learning for Graph Partitioning and MatchingCode0
The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning—0
PyTorch-BigGraph: A Large-scale Graph Embedding SystemCode0
GAP: Generalizable Approximate Graph Partitioning FrameworkCode0
Massively Parallel Benders Decomposition for Correlation Clustering—0
Learning Space Partitions for Nearest Neighbor SearchCode0
COSINE: Compressive Network Embedding on Large-scale Information Networks—0
From Free Text to Clusters of Content in Health Records: An Unsupervised Graph Partitioning Approach—0
Mean-field theory of graph neural networks in graph partitioning—0
Towards Efficient Large-Scale Graph Neural Network Computing—0
The Mutex Watershed: Efficient, Parameter-Free Image Partitioning—0
Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation—0
Content-driven, unsupervised clustering of news articles through multiscale graph partitioning—0
Supporting Very Large Models using Automatic Dataflow Graph Partitioning—0
Algorithms for metric learning via contrastive embeddings—0
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