Corpus ID: 869110

Optimal Cluster Recovery in the Labeled Stochastic Block Model

@inproceedings{Yun2016OptimalCR,
  title={Optimal Cluster Recovery in the Labeled Stochastic Block Model},
  author={SeYoung Yun and Alexandre Prouti{\`e}re},
  booktitle={NIPS},
  year={2016}
}
  • SeYoung Yun, Alexandre Proutière
  • Published in NIPS 2016
  • Computer Science, Mathematics
  • We consider the problem of community detection or clustering in the labeled Stochastic Block Model (LSBM) with a finite number $K$ of clusters of sizes linearly growing with the global population of items $n$. Every pair of items is labeled independently at random, and label $\ell$ appears with probability $p(i,j,\ell)$ between two items in clusters indexed by $i$ and $j$, respectively. The objective is to reconstruct the clusters from the observation of these random labels. Clustering under… CONTINUE READING

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 38 CITATIONS

    Fast Randomized Semi-Supervised Clustering

    VIEW 1 EXCERPT
    CITES BACKGROUND

    Optimal Sampling and Clustering in the Stochastic Block Model

    VIEW 10 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Clustering in Block Markov Chains

    VIEW 1 EXCERPT
    CITES BACKGROUND

    Community Detection and Stochastic Block Models

    • Emmanuel Abbe
    • Computer Science
    • Found. Trends Commun. Inf. Theory
    • 2018

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 27 REFERENCES

    Community Detection via Random and Adaptive Sampling

    VIEW 4 EXCERPTS

    Exact Recovery in the Stochastic Block Model