From the 2 of 16 linked papers with an AI index.
16 papers
An RDT based confirmation of Lehner's formula for Kronecker-Gaussian matrices
Mihailo Stojnic
The paper uses Random Duality Theory to rederive Lehner’s formula for the spectral edges of Kronecker‑Gaussian matrices, offering an alternative proof of strong asymptotic freeness…
Precise sample covariance spectral norm error -- an RDT view
Mihailo Stojnic
The paper derives the exact limiting value of the spectral‑norm error of sample covariance matrices for centered Gaussian data, using a Random Duality Theory framework that provide…
An RDT based approach to large deviations of Wishart and Wigner matrices spectral edges
Mihailo Stojnic
We present a novel methodology for studying \emph{large deviations principles} (LDPs) of random matrices. By utilizing a partially lifted variant of \emph{random duality theory} (R…
Ultrametric OGP - parametric RDT \emph{symmetric} binary perceptron connection
Mihailo Stojnic
In [97,99,100], an fl-RDT framework is introduced to characterize \emph{statistical computational gaps} (SCGs). Studying \emph{symmetric binary perceptrons} (SBPs), [100] obtained…
Parametric RDT approach to computational gap of symmetric binary perceptron
Mihailo Stojnic
We study potential presence of statistical-computational gaps (SCG) in symmetric binary perceptrons (SBP) via a parametric utilization of \emph{fully lifted random duality theory}…
Binary perceptron computational gap -- a parametric fl RDT view
Mihailo Stojnic
Recent studies suggest that asymmetric binary perceptron (ABP) likely exhibits the so-called statistical-computational gap characterized with the appearance of two phase transition…