Open access
Date
2022-05-06Type
- Journal Article
Abstract
Semidefinite programming is an important tool to tackle several problems in data science and signal processing, including clustering and community detection. However, semidefinite programs are often slow in practice, so speed up techniques such as sketching are often considered. In the context of community detection in the stochastic block model, Mixon and Xie (IEEE Trans Inform Theory 67(10): 6832–6840, 2021) have recently proposed a sketching framework in which a semidefinite program is solved only on a subsampled subgraph of the network, giving rise to significant computational savings. In this short paper, we provide a positive answer to a conjecture of Mixon and Xie about the statistical limits of this technique for the stochastic block model with two balanced communities. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000547746Publication status
publishedExternal links
Journal / series
Sampling Theory, Signal Processing, and Data AnalysisVolume
Pages / Article No.
Publisher
SpringerSubject
Community detection; Clustering algorithms; Graph and network theory; Semidefinite programmingOrganisational unit
09679 - Bandeira, Afonso / Bandeira, Afonso
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