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We propose an efficient meta-algorithm for Bayesian estimation problems that is based on low-degree polynomials, semidefinite programming, and tensor decomposition.
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Jess Banks, Cristopher Moore, Joe Neeman, and Praneeth Netrapalli, Information-theoretic thresholds for community detection in sparse networks , COLT, JMLR Workshop and Conference Proceedings, vol. 49, JMLR.org, 2016, pp. 383–416
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Jess Banks, Robert Kleinberg, and Cristopher Moore, The lovász theta function for random regular graphs and community detection in the hard regime , APPROX-RANDOM, LIPIcs, vol. 81, Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2017, pp. 28:1–28:22
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