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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 1–25 of 208 papers

TitleStatusHype
DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic PotentialsCode2
Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and LocalizationCode2
Upsampling DINOv2 features for unsupervised vision tasks and weakly supervised materials segmentationCode1
A Structure-Aware Framework for Learning Device Placements on Computation GraphsCode1
CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised TransformersCode1
Unleashing Graph Partitioning for Large-Scale Nearest Neighbor SearchCode1
Self-supervised Few-shot Learning for Semantic Segmentation: An Annotation-free ApproachCode1
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate CommunicationCode1
Task-specific Scene Structure RepresentationsCode1
Learning to Solve Combinatorial Graph Partitioning Problems via Efficient ExplorationCode1
Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and SimplicityCode1
RAMA: A Rapid Multicut Algorithm on GPUCode1
Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural NetworksCode1
Reformulating DOVER-Lap Label Mapping as a Graph Partitioning ProblemCode1
Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object TrackingCode1
Accurate and versatile 3D segmentation of plant tissues at cellular resolutionCode1
Graph Neural Network Based Coarse-Grained Mapping PredictionCode1
Generalized Spectral Clustering via Gromov-Wasserstein LearningCode1
PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed TrainingCode0
Demystifying Distributed Training of Graph Neural Networks for Link PredictionCode0
Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning—0
A Graph-Partitioning Based Continuous Optimization Approach to Semi-supervised Clustering Problems—0
Node-level Contrastive Unlearning on Graph Neural Networks—0
WaveGAS: Waveform Relaxation for Scaling Graph Neural Networks—0
Dual-Bounded Nonlinear Optimal Transport for Size Constrained Min Cut Clustering—0
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