SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–60 of 208 papers

TitleStatusHype
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks—0
BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs—0
Efficient Partitioning Method of Large-Scale Public Safety Spatio-Temporal Data based on Information Loss Constraints—0
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate CommunicationCode1
Creating Multi-Level Skill Hierarchies in Reinforcement LearningCode0
Fast Algorithms for Directed Graph Partitioning Using Flows and Reweighted Eigenvalues—0
One-step Bipartite Graph Cut: A Normalized Formulation and Its Application to Scalable Subspace Clustering—0
Distributed Compressed Sparse Row Format for Spiking Neural Network Simulation, Serialization, and Interoperability—0
Inductive Graph UnlearningCode0
Distributed Graph Embedding with Information-Oriented Random WalksCode0
Show:102550
← PrevPage 6 of 21Next →

No leaderboard results yet.