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Near-field communications: A tutorial review
Extremely large-scale antenna arrays, tremendously high frequencies, and new types of
antennas are three clear trends in multi-antenna technology for supporting the sixth …
antennas are three clear trends in multi-antenna technology for supporting the sixth …
Recent exact and asymptotic results for products of independent random matrices
In this review we summarise recent results for the complex eigenvalues and singular values
of finite products of finite size random matrices, their correlation functions and asymptotic …
of finite products of finite size random matrices, their correlation functions and asymptotic …
The low-rank simplicity bias in deep networks
Modern deep neural networks are highly over-parameterized compared to the data on which
they are trained, yet they often generalize remarkably well. A flurry of recent work has asked …
they are trained, yet they often generalize remarkably well. A flurry of recent work has asked …
Triple descent and the two kinds of overfitting: Where & why do they appear?
A recent line of research has highlighted the existence of a``double descent''phenomenon in
deep learning, whereby increasing the number of training examples N causes the …
deep learning, whereby increasing the number of training examples N causes the …
Contrasting random and learned features in deep Bayesian linear regression
Understanding how feature learning affects generalization is among the foremost goals of
modern deep learning theory. Here, we study how the ability to learn representations affects …
modern deep learning theory. Here, we study how the ability to learn representations affects …
Eigenvalue distribution of some nonlinear models of random matrices
This paper is concerned with the asymptotic empirical eigenvalue distribution of some non
linear random matrix ensemble. More precisely we consider M= 1 m YY∗ with Y= f (WX) …
linear random matrix ensemble. More precisely we consider M= 1 m YY∗ with Y= f (WX) …
Singular values of products of Ginibre random matrices, multiple orthogonal polynomials and hard edge scaling limits
Abstract Akemann, Ipsen and Kieburg recently showed that the squared singular values of
products of M rectangular random matrices with independent complex Gaussian entries are …
products of M rectangular random matrices with independent complex Gaussian entries are …
Statistical limits of dictionary learning: random matrix theory and the spectral replica method
We consider increasingly complex models of matrix denoising and dictionary learning in the
Bayes-optimal setting, in the challenging regime where the matrices to infer have a rank …
Bayes-optimal setting, in the challenging regime where the matrices to infer have a rank …
A review of exact results for fluctuation formulas in random matrix theory
Covariances and variances of linear statistics of a point process can be written as integrals
over the truncated two-point correlation function. When the point process consists of the …
over the truncated two-point correlation function. When the point process consists of the …
Meet andréief, bordeaux 1886, and andreev, kharkov 1882–1883
The paper “Note sur une relation entre les intégrales définies des produits des fonctions” by
C. Andréief is an often cited paper in random matrix theory, due to it containing what is now …
C. Andréief is an often cited paper in random matrix theory, due to it containing what is now …