33 citations · 133 across the 43 of their papers we have counts for
5 papers · 1 filter
High-Dimensional Privacy-Utility Dynamics of Noisy Stochastic Gradient Descent on Least Squares
Shurong Lin, Eric D. Kolaczyk, Adam Smith +1
The interplay between optimization and privacy has become a central theme in privacy-preserving machine learning. Noisy stochastic gradient descent (SGD) has emerged as a cornersto…
Eigenvalue distribution of the Neural Tangent Kernel in the quadratic scaling
Lucas Benigni, Elliot Paquette
We compute the asymptotic eigenvalue distribution of the neural tangent kernel of a two-layer neural network under a specific scaling of dimension. Namely, if $X\in\mathbb{R}^{n\ti…
Bulk asymptotics of the Gaussian -ensemble characteristic polynomial
Gaultier Lambert, Elliot Paquette
The Gaussian -ensemble (GE) is a fundamental model in random matrix theory. In this paper, we provide a comprehensive asymptotic description of the characteristic polynomial…
The Fourier coefficients of the holomorphic multiplicative chaos in the limit of large frequency
Joseph Najnudel, Elliot Paquette, Nick Simm +1
The holomorphic multiplicative chaos (HMC) is a holomorphic analogue of the Gaussian multiplicative chaos. It arises naturally as the limit in large matrix size of the characterist…
Operator level soft edge to bulk transition in -ensembles via canonical systems
Vincent Painchaud, Elliot Paquette
The stochastic Airy and sine operators, which are respectively a random Sturm-Liouville operator and a random Dirac operator, characterize the soft edge and bulk scaling limits of…