On Friday, October 16, at 14h30 in Aula Dal Passo in the Math Department of the University of Rome Tor Vergata, RoMaDS (https://www.mat.uniroma2.it/~rds/events.php) will host
Michaël Unser (EPFL) with the colloquium
“Variational splines and stochastic processes: From kernel methods (and Norbert Wiener) to ReLU networks”
Abstract: The Wiener (MMSE) estimator of a Brownian motion (a.k.a. Wiener process) from noisy samples is a linear spline. Similarly, a variational reconstruction problem with second-order total variation regularization yields an adaptive linear spline solution. Deep ReLU networks can also be interpreted as spline functions, albeit in higher-dimensional spaces. In this talk, I will show how these seemingly disparate results are unified through a common variational framework. I will further relate this perspective to stochastic modeling: kernel methods naturally correspond to Gaussian processes, while neural network approaches can be interpreted in terms of sparse stochastic processes.
We encourage in-person partecipation. Should you be unable to come, here is the link to the Teams streaming: