Stochastic block model: Difference between revisions

Revision as of 12:30, 30 October 2021

Revision as of 19:19, 9 March 2022

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| date = 2018 |doi = 10.1126/sciadv.aaq1360 | volume=4 | issue=7

|pmid=30035215 |pmc=6051742 |arxiv=1708.01677 |bibcode=2018SciA....4.1360G }}</ref> In a network of documents and words, Stochastic block model can identify topics: group of words with a similar meaning.

== DARPA/MIT/AWS Graph Challenge: streaming stochastic block partition ==

GraphChallenge<ref>[http://graphchallenge.mit.edu] DARPA/MIT/AWS Graph Challenge</ref> encourages community approaches to developing new solutions for analyzing graphs and sparse data derived from social media, sensor feeds, and scientific data to enable relationships between events to be discovered as they unfold in the field. Streaming stochastic block partition is one of the challenges since 2017

<ref>[http://graphchallenge.mit.edu/champions] DARPA/MIT/AWS Graph Challenge Champions</ref>, where preconditioned [[spectral clustering]] has demonstrated outstanding performance compared to the base algorithm, matching its quality of clusters while being multiple orders of magnitude faster.<ref>{{cite journal

| author1 = David Zhuzhunashvili |author2 = Andrew Knyazev

| title = Preconditioned spectral clustering for stochastic block partition streaming graph challenge (Preliminary version at arXiv.)

| journal=2017 IEEE High Performance Extreme Computing Conference (HPEC)

| date = 2017 |doi = 10.1109/HPEC.2017.8091045}}</ref>

==See also==