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20242026
most citedUniversality of empirical risk minimization

23 citations · 23 across the 2 of their papers we have counts for

collaborators

10 papers

math.PR2026

Free energy of Ising models under a spectral condition

Andrea Montanari, Michael Ren

A sequence of sparse weighted graphs indexed by the number of vertices is said to be left-convergent if all (suitably weighted) subgraph counts converge to a lim…

math.ST202623 cited

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…

math.PR2026

The high-dimensional asymptotics of first order methods with random data

Michael Celentano, Chen Cheng, Andrea Montanari

We study a class of deterministic flows in , parametrized by a random matrix with i.i.d. centered subgaussian…

cs.LG2025

Sampling, Diffusions, and Stochastic Localization

Andrea Montanari

Diffusions are a successful technique to sample from high-dimensional distributions. The target distribution can be either explicitly given or learnt from a collection of samples.…

math.ST2025

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…

stat.ML2025

Overparametrized linear dimensionality reductions: From projection pursuit to two-layer neural networks

Andrea Montanari, Kangjie Zhou

Given a cloud of data points in , consider all projections onto -dimensional subspaces of and, for each such projection, the empirical distribut…