no code implementations • 25 Jul 2023 • Andrea Della Vecchia, Kibidi Neocosmos, Daniel B. Larremore, Cristopher Moore, Caterina De Bacco
We present a physics-inspired method for inferring dynamic rankings in directed temporal networks - networks in which each directed and timestamped edge reflects the outcome and timing of a pairwise interaction.
no code implementations • 17 Apr 2023 • Sofiane Tanji, Andrea Della Vecchia, François Glineur, Silvia Villa
Kernel methods provide a powerful framework for non parametric learning.
no code implementations • 4 Dec 2022 • Andrea Della Vecchia, Ernesto de Vito, Lorenzo Rosasco
We study a natural extension of classical empirical risk minimization, where the hypothesis space is a random subspace of a given space.
no code implementations • 31 May 2022 • Pierre Laforgue, Andrea Della Vecchia, Nicolò Cesa-Bianchi, Lorenzo Rosasco
We introduce and analyze AdaTask, a multitask online learning algorithm that adapts to the unknown structure of the tasks.
no code implementations • 17 Jun 2020 • Andrea Della Vecchia, Jaouad Mourtada, Ernesto de Vito, Lorenzo Rosasco
We study a natural extension of classical empirical risk minimization, where the hypothesis space is a random subspace of a given space.