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https://issues.apache.org/jira/browse/FLINK-1707?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15421162#comment-15421162
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Vasia Kalavri commented on FLINK-1707:
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Hi [~joseprupi],
I haven't had time to look at your example yet :/
Regarding your first question, if you skip damping, is it guaranteed that the
algorithm still converges and produces the correct value? It would just
converge more slowly?
Regarding your other questions, I think that's it's more natural to have the
graph itself as input with the similarities as edge values. This way (1) you
won't need to convert any matrix to a graph and (2) nodes have non-zero
similarities with their neighbors only. Does this make sense?
> Add an Affinity Propagation Library Method
> ------------------------------------------
>
> Key: FLINK-1707
> URL: https://issues.apache.org/jira/browse/FLINK-1707
> Project: Flink
> Issue Type: New Feature
> Components: Gelly
> Reporter: Vasia Kalavri
> Assignee: Josep Rubió
> Priority: Minor
> Labels: requires-design-doc
> Attachments: Binary_Affinity_Propagation_in_Flink_design_doc.pdf
>
>
> This issue proposes adding the an implementation of the Affinity Propagation
> algorithm as a Gelly library method and a corresponding example.
> The algorithm is described in paper [1] and a description of a vertex-centric
> implementation can be found is [2].
> [1]: http://www.psi.toronto.edu/affinitypropagation/FreyDueckScience07.pdf
> [2]: http://event.cwi.nl/grades2014/00-ching-slides.pdf
> Design doc:
> https://docs.google.com/document/d/1QULalzPqMVICi8jRVs3S0n39pell2ZVc7RNemz_SGA4/edit?usp=sharing
> Example spreadsheet:
> https://docs.google.com/spreadsheets/d/1CurZCBP6dPb1IYQQIgUHVjQdyLxK0JDGZwlSXCzBcvA/edit?usp=sharing
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