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 21–30 of 208 papers

TitleStatusHype
Distributed Training of Large Graph Neural Networks with Variable Communication Rates—0
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph PartitioningCode0
FastGAS: Fast Graph-based Annotation Selection for In-Context Learning—0
A random-key GRASP for combinatorial optimizationCode0
A Structure-Aware Framework for Learning Device Placements on Computation GraphsCode1
Exploring Key Point Analysis with Pairwise Generation and Graph PartitioningCode0
CATGNN: Cost-Efficient and Scalable Distributed Training for Graph Neural Networks—0
A Clustering Method with Graph Maximum Decoding Information—0
CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised TransformersCode1
Unleashing Graph Partitioning for Large-Scale Nearest Neighbor SearchCode1
Show:102550
← PrevPage 3 of 21Next →

No leaderboard results yet.