4 papers
Learning Ergodic Dynamical Systems from a Finite Trajectory
Oleksii Kachaiev, Silvia Villa, Lorenzo Rosasco
We consider the problem of learning from a single finite trajectory of an ergodic stochastic dynamical system. More precisely, we study discrete-time autonomous stochastic systems…
Optimization Insights into Deep Diagonal Linear Networks
Hippolyte Labarrière, Cesare Molinari, Lorenzo Rosasco +2
Gradient-based methods successfully train highly overparameterized models in practice, even though the associated optimization problems are markedly nonconvex. Understanding the me…
Iterative regularization in classification via hinge loss diagonal descent
Vassilis Apidopoulos, Tomaso Poggio, Lorenzo Rosasco +1
Iterative regularization is a classic idea in regularization theory, that has recently become popular in machine learning. On the one hand, it allows to design efficient algorithms…
Stochastic Zeroth order Descent with Structured Directions
Marco Rando, Cesare Molinari, Silvia Villa +1
We introduce and analyze Structured Stochastic Zeroth order Descent (S-SZD), a finite difference approach that approximates a stochastic gradient on a set of orthogonal d…