Data · dataset · 2015
A Localized Implementation of the Iterative Proportional Scaling Procedure For Gaussian Graphical Models
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In this paper, we propose localized implementations of the iterative proportional scaling (IPS) procedure by the strategy of partitioning cliques for computing maximum likelihood estimations in large Gaussian graphical models.
Description
We first divide the set of cliques into several non-overlapping and non-empty blocks, and then adjust clique marginals in each block locally. Thus, high order matrix operations can be avoided and the IPS procedure is accelerated.
We modify the Swendsen-Wang Algorithm and apply the simulated annealing algorithm to find an approximation to the optimal partition which leads to the least complexity. This strategy of partitioning cliques can also speed up the existing IIPS and IHT procedures. Numerical experiments are presented to demonstrate the competitive performance of our new implementations and strategies.
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Where it is published
- Repository landing page tandf.figshare.com/articles/dataset/A_Localized_Implementation_of_the_Iterative_P… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.987097.v1 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1080/10618600.2014.900499 doi.org/10.1080/10618600.2014.900499 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.987097.v1 ↗
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- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.987097.v1 ↗
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Topics
- Stated by source
- Mathematics
- From keywords
- Life Sciences · Mathematics & Statistics
- Inferred from text
- Large and complex data theory 79%
Related
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.987097.v1 | 10 d ago | JSON v1 |
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| concepts[field].local:field:life-sciences | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Biological Sciences'] |
| concepts[field].local:field:mathematics-statistics | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Mathematics'] |
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