2.5k citations · 10k across the 171 of their papers we have counts for
34 papers · 1 filter
Posterior Sampling in High Dimension via Diffusion Processes
Andrea Montanari, Yuchen Wu
Sampling from the posterior is a key technical problem in Bayesian statistics. Rigorous guarantees are difficult to obtain for Markov Chain Monte Carlo algorithms of common use. In…
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}^{\to…
Fundamental Limits of Low-Rank Matrix Estimation with Diverging Aspect Ratios
Andrea Montanari, Yuchen Wu
We consider the problem of estimating the factors of a low-rank matrix, when this is corrupted by additive Gaussian noise. A special example of our setting corresponds…
Dimension free ridge regression
Chen Cheng, Andrea Montanari
Random matrix theory has become a widely useful tool in high-dimensional statistics and theoretical machine learning. However, random matrix theory is largely focused on the propor…
A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists
Andrea Montanari, Subhabrata Sen
This tutorial is based on lecture notes written for a class taught in the Statistics Department at Stanford in the Winter Quarter of 2017. The objective was to provide a working kn…
Universality of empirical risk minimization
Andrea Montanari, Basil Saeed
We study a general class of optimization problems with decision variable and cost function which is the sum of terms, each dependent…