High-dimensional dynamics of generalization error in neural networks

Benign overfitting in linear regression

(2020) Peter L. Bartlett et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Reconciling modern machine-learning practice and the classical bias–variance trade-off

(2019) Mikhail Belkin et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Statistical Mechanics of Deep Learning

(2019) Yasaman Bahri et al.   Annual Review of Condensed Matter Physics

A mean field view of the landscape of two-layer neural networks

(2018) Song Mei et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Statistical Mechanics of Optimal Convex Inference in High Dimensions

(2016) Madhu Advani et al.   Physical Review X

Deep learning

(2015) Yann LeCun et al.   NATURE

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Universality of covariance matrices

(2014) Natesh S. Pillai et al.   ANNALS OF APPLIED PROBABILITY

Statistical mechanics of complex neural systems and high dimensional data

(2013) Madhu Advani et al.   JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT

The singular values and vectors of low rank perturbations of large rectangular random matrices

(2012) Florent Benaych-Georges et al.   JOURNAL OF MULTIVARIATE ANALYSIS

The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices

(2011) Florent Benaych-Georges et al.   ADVANCES IN MATHEMATICS

Dynamics of learning near singularities in radial basis function networks

(2008) Haikun Wei et al.   NEURAL NETWORKS

Dynamics of Learning Near Singularities in Layered Networks

(2007) Haikun Wei et al.   NEURAL COMPUTATION