Partition-Merge: Distributed Inference and Modularity Optimization

Partition-Merge: Distributed Inference and Modularity Optimization

This paper presents a novel meta-algorithm, Partition-Merge (PM), which takes existing centralized algorithms for graph computation and makes them distributed and faster. In a nutshell, PM divides the graph into small subgraphs using our novel randomized partitioning scheme, runs the centralized alg...

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Bibliographic Details
Main Authors: Vincent Blondel, Kyomin Jung, Pushmeet Kohli, Devavrat Shah, Seungpil Won
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Approximate MAP
graphical model
modularity optimization
partition
Online Access:https://ieeexplore.ieee.org/document/9393375/

Internet

https://ieeexplore.ieee.org/document/9393375/

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