5 papers · 1 filter
Is it easier to count communities than find them?
Cynthia Rush, Fiona Skerman, Alexander S. Wein +1
Random graph models with community structure have been studied extensively in the literature. For both the problems of detecting and recovering community structure, an interesting…
Precise Error Rates for Computationally Efficient Testing
Ankur Moitra, Alexander S. Wein
We revisit the fundamental question of simple-versus-simple hypothesis testing with an eye towards computational complexity, as the statistically optimal likelihood ratio test is o…
Statistical inference of a ranked community in a directed graph
Dmitriy Kunisky, Daniel A. Spielman, Alexander S. Wein +1
We study the problem of detecting or recovering a planted ranked subgraph from a directed graph, an analog for directed graphs of the well-studied planted dense subgraph model. We…
Equivalence of Approximate Message Passing and Low-Degree Polynomials in Rank-One Matrix Estimation
Andrea Montanari, Alexander S. Wein
We consider the problem of estimating an unknown parameter vector , given noisy observations ${\boldsymbol Y} = {\boldsymbol θ}{\boldsymbol θ}^{…
Tensor cumulants for statistical inference on invariant distributions
Dmitriy Kunisky, Cristopher Moore, Alexander S. Wein
Many problems in high-dimensional statistics appear to have a statistical-computational gap: a range of values of the signal-to-noise ratio where inference is information-theoretic…