4 citations · 4 across the 12 of their papers we have counts for
6 papers · 1 filter
Optimization by Reparametrization: Time-Warped Mirror Flows with Singular Geometry
Cristian Vega, Cesare Molinari, Lorenzo Rosasco +1
Solving data-driven problems requires defining complex models and fitting them to data, neural networks being a motivating example. The fitting procedure can be seen as an optimiza…
Langevin for Nonconvex Optimization: Exact, Inexact and Zeroth-Order
Emanuele Naldi, Marco Rando, Lorenzo Rosasco +1
We study Langevin-based methods for non-convex optimization under smoothness and dissipativity assumptions, focusing on non-asymptotic expected excess-risk bounds rather than sampl…
Learning to control switching nonlinear systems with Koopman operator regression
Edoardo Caldarelli, Oleksii Kachaiev, Cesare Molinari +1
In this work, we consider the identification and control of nonlinear systems with finite action spaces. The unknown dynamics are estimated from finite samples with Koopman operato…
A Proximal Stochastic Variance Reduced Zeroth-order Algorithm using Structured Finite-Differences
Marco Rando, Cheik Traoré, Cesare Molinari +2
Minimizing finite sums of functions is a central problem in optimization, arising in numerous practical applications. Such problems are commonly addressed using first-order optimiz…
A Structured Tour of Optimization with Finite Differences
Marco Rando, Cesare Molinari, Lorenzo Rosasco +1
Finite-difference methods are widely used for zeroth-order optimization in settings where gradient information is unavailable or expensive to compute. These procedures mimic first-…
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
Edoardo Caldarelli, Antoine Chatalic, Adrià Colomé +4
In this paper, we study how the Koopman operator framework can be combined with kernel methods to effectively control nonlinear dynamical systems. While kernel methods have typical…