17 citations · 44 across the 11 of their papers we have counts for
5 papers · 1 filter
Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture Models
Anya Katsevich, Afonso Bandeira
We derive an asymptotic expansion for the log likelihood of Gaussian mixture models (GMMs) with equal covariance matrices in the low signal-to-noise regime. The expansion reveals a…
The Average-Case Time Complexity of Certifying the Restricted Isometry Property
Yunzi Ding, Dmitriy Kunisky, Alexander S. Wein +1
In compressed sensing, the restricted isometry property (RIP) on sensing matrices (where ) guarantees efficient reconstruction of sparse vectors. A matrix has t…
Computationally efficient sparse clustering
Matthias Löffler, Alexander S. Wein, Afonso S. Bandeira
We study statistical and computational limits of clustering when the means of the centres are sparse and their dimension is possibly much larger than the sample size. Our theoretic…
Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio
Dmitriy Kunisky, Alexander S. Wein, Afonso S. Bandeira
These notes survey and explore an emerging method, which we call the low-degree method, for predicting and understanding statistical-versus-computational tradeoffs in high-dimensio…
Optimality and Sub-optimality of PCA I: Spiked Random Matrix Models
Amelia Perry, Alexander S. Wein, Afonso S. Bandeira +1
A central problem of random matrix theory is to understand the eigenvalues of spiked random matrix models, introduced by Johnstone, in which a prominent eigenvector (or "spike") is…