Over the past few years, the number and volume of data sources in healthcare databases
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …

We consider the problem of estimating an unknown parameter vector θ∈ R n, given noisy
observations Y= θ θ T/n+ Z of the rank-one matrix θ θ T, where Z has independent Gaussian …

A precise high-dimensional asymptotic theory for boosting and minimum-l1-norm
interpolated classifiers Page 1 The Annals of Statistics 2022, Vol. 50, No. 3, 1669–1695 …

Computational barriers to estimation from low-degree polynomials Page 1 The Annals of
Statistics 2022, Vol. 50, No. 3, 1833–1858 https://doi.org/10.1214/22-AOS2179 © Institute of …

In this work, we study the problem of community detection in the stochastic block model with
adversarial node corruptions. Our main result is an efficient algorithm that can tolerate an ϵ …

Fundamental barriers to high-dimensional regression with convex penalties Page 1 The
Annals of Statistics 2022, Vol. 50, No. 1, 170–196 https://doi.org/10.1214/21-AOS2100 © …

Approximate message passing (AMP) is a family of iterative algorithms that generalize
matrix power iteration. AMP algorithms are known to optimally solve many average-case …

Gaussian mixture block models are distributions over graphs that strive to model modern
networks: to generate a graph from such a model, we associate each vertex $ i $ with a …

Detection of a planted dense subgraph in a random graph is a fundamental statistical and
computational problem that has been extensively studied in recent years. We study a …

Suppose we are given an n-dimensional order-3 symmetric tensor T∈(ℝ n)⊗ 3 that is the
sum of r random rank-1 terms. The problem of recovering the rank-1 components is possible …