3 citations · 8 across the 11 of their papers we have counts for
12 papers
Variational formula for the logarithmic potential of free additive convolutions
Francesco Concetti, David Belius, Giuseppe Genovese
We establish a general variational formula for the logarithmic potential of the free additive convolution of two compactly supported probability measure on . The formula is giv…
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression
Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios +1
This paper conducts a comprehensive study of the learning curves of kernel ridge regression (KRR) under minimal assumptions. Our contributions are three-fold: 1) we analyze the rol…
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios +1
We derive new bounds for the condition number of kernel matrices, which we then use to enhance existing non-asymptotic test error bounds for kernel ridgeless regression (KRR) in th…
On the determinant in Bray-Moore's TAP complexity formula
David Belius, Francesco Concetti, Giuseppe Genovese
In the computation of the TAP complexity, originally carried out by Bray and Moore, a fundamental step is to calculate the determinant of a random Hessian. As the replica method do…
A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression
Tin Sum Cheng, Aurelien Lucchi, Ivan Dokmanić +2
Existing statistical learning guarantees for general kernel regressors often yield loose bounds when used with finite-rank kernels. Yet, finite-rank kernels naturally appear in sev…
Fluctuations of the ground state of the spiked spherical Sherrington-Kirkpatrick model
David Belius, Leon Fröber
The Sherrington-Kirkpatrick Hamiltonian is a random quadratic function on the high-dimensional sphere. This article studies the ground state (i.e. maximum) of this Hamiltonian with…