activity
20192024
most citedDeterministic equivalent and error universality of deep random features learning

3 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

math.PR2024

Matrix Concentration Inequalities and Free Probability II. Two-sided Bounds and Applications

Afonso S. Bandeira, Giorgio Cipolloni, Dominik Schröder +1

The first paper in this series introduced a new family of nonasymptotic matrix concentration inequalities that sharply capture the spectral properties of very general random matric…

stat.ML2023★ 3 cited

Deterministic equivalent and error universality of deep random features learning

Dominik Schröder, Hugo Cui, Daniil Dmitriev +1

This manuscript considers the problem of learning a random Gaussian network function using a fully connected network with frozen intermediate layers and trainable readout layer. Th…

math.PR2023

Optimal Lower Bound on Eigenvector Overlaps for non-Hermitian Random Matrices

Giorgio Cipolloni, László Erdős, Joscha Henheik +1

We consider large non-Hermitian matrices with an additive independent, identically distributed (i.i.d.) noise for each matrix elements. We show that already a small noi…

cs.NE2022★ 3 cited

Switching between Numerical Black-box Optimization Algorithms with Warm-starting Policies

Dominik Schröder, Diederick Vermetten, Hao Wang +2

When solving optimization problems with black-box approaches, the algorithms gather valuable information about the problem instance during the optimization process. This informatio…

math.PR2019

Towards the bulk universality of non-Hermitian random matrices

Giorgio Cipolloni, László Erdős, Dominik Schröder

We consider the non-Hermitian analogue of the celebrated Wigner-Dyson-Mehta bulk universality phenomenon, i.e. that in the bulk the local eigenvalue statistics of a large random ma…