Bayesian estimation from few samples: community detection and related problems

We propose an efficient meta-algorithm for Bayesian estimation problems that is based on low-degree polynomials, semidefinite programming, and tensor decomposition. algorithm is inspired by recent lower bound constructions for sum-of-squares and related to the method of moments. focus is on sample complexity bounds that are as tight as ...More