378 citations · 1.2k across the 40 of their papers we have counts for
6 papers · 1 filter
Construction of optimal spectral methods in phase retrieval
Antoine Maillard, Florent Krzakala, Yue M. Lu +1
We consider the phase retrieval problem, in which the observer wishes to recover a -dimensional real or complex signal from the (possibly noisy) observation o…
Universality Laws for High-Dimensional Learning with Random Features
Hong Hu, Yue M. Lu
We prove a universality theorem for learning with random features. Our result shows that, in terms of training and generalization errors, a random feature model with a nonlinear ac…
A Precise Performance Analysis of Learning with Random Features
Oussama Dhifallah, Yue M. Lu
We study the problem of learning an unknown function using random feature models. Our main contribution is an exact asymptotic analysis of such learning problems with Gaussian data…
The Limiting Poisson Law of Massive MIMO Detection with Box Relaxation
Hong Hu, Yue M. Lu
Estimating a binary vector from noisy linear measurements is a prototypical problem for MIMO systems. A popular algorithm, called the box-relaxation decoder, estimates the target s…
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization
Benjamin Aubin, Florent Krzakala, Yue M. Lu +1
We consider a commonly studied supervised classification of a synthetic dataset whose labels are generated by feeding a one-layer neural network with random iid inputs. We study th…
The role of regularization in classification of high-dimensional noisy Gaussian mixture
Francesca Mignacco, Florent Krzakala, Yue M. Lu +1
We consider a high-dimensional mixture of two Gaussians in the noisy regime where even an oracle knowing the centers of the clusters misclassifies a small but finite fraction of th…