← Search

Cesare Molinari

2 accepted papers

2023

An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization

NeurIPS 2023poster

Finite-difference methods are a class of algorithms designed to solve black-box optimization problems by approximating a gradient of the target function on a set of directions. In black-box optimization, the non-smooth setting is particularly relevant since, in practice, differentiability and smooth…

Cited by 18SourcePDFScholar
2021

Iterative regularization for convex regularizers

AISTATS 2021poster

We study iterative regularization for linear models, when the bias is convex but not necessarily strongly convex. We characterize the stability properties of a primal-dual gradient based approach, analyzing its convergence in the presence of worst case deterministic noise. As a main example, we spec…

Cited by 21SourcePDFScholar