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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 151–175 of 208 papers

TitleStatusHype
Improved Image Boundaries for Better Video Segmentation—0
Incorporating Road Networks into Territory Design—0
Integrating Graph Partitioning and Matching for Trajectory Analysis in Video Surveillance—0
Joint Optimization of Scheduling and Routing in Multicast Wireless Ad-Hoc Network Using Soft Graph Coloring and Non-linear Cubic Games—0
Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed—0
Kernel k-Groups via Hartigan's Method—0
Large Scale Training of Graph Neural Networks for Optimal Markov-Chain Partitioning Using the Kemeny Constant—0
Distributed Evolutionary Graph PartitioningCode0
Distributed Graph Embedding with Information-Oriented Random WalksCode0
A Min-max Cult Algorithm for Graph Partitioning and Data ClusteringCode0
Think Locally, Act Globally: Perfectly Balanced Graph PartitioningCode0
Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph ClusteringCode0
Improving Coarsening Schemes for Hypergraph Partitioning by Exploiting Community StructureCode0
A parameter-free graph reduction for spectral clustering and SpectralNetCode0
Inductive Graph UnlearningCode0
Parallel Graph Partitioning for Complex NetworksCode0
Fine-tuning Partition-aware Item Similarities for Efficient and Scalable RecommendationCode0
Intel nGraph: An Intermediate Representation, Compiler, and Executor for Deep LearningCode0
PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed TrainingCode0
Ego-splitting Framework: from Non-Overlapping to Overlapping ClustersCode0
Revisiting Surgical Instrument Segmentation Without Human Intervention: A Graph Partitioning ViewCode0
Robust Fair Clustering: A Novel Fairness Attack and Defense FrameworkCode0
Towards Faster Graph Partitioning via Pre-training and Inductive InferenceCode0
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph PartitioningCode0
Exploring Key Point Analysis with Pairwise Generation and Graph PartitioningCode0
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