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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 91–100 of 208 papers

TitleStatusHype
WawPart: Workload-Aware Partitioning of Knowledge Graphs—0
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks—0
Generalized Spectral Clustering for Directed and Undirected Graphs—0
SUGAR: Efficient Subgraph-level Training via Resource-aware Graph Partitioning—0
Deep Learning and Spectral Embedding for Graph Partitioning—0
Trading Quality for Efficiency of Graph Partitioning: An Inductive Method across Graphs—0
A Design Flow for Mapping Spiking Neural Networks to Many-Core Neuromorphic Hardware—0
Stateless actor-critic for instance segmentation with high-level priors—0
xER: An Explainable Model for Entity Resolution using an Efficient Solution for the Clique Partitioning Problem—0
_2-norm Flow Diffusion in Near-Linear Time—0
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