Elenco seminari del ciclo di seminari
“GEOMETRIA E DEEP LEARNING”

In questo ciclo di seminari verranno esposte alcune tematiche correlate all'uso di metodi geometrici nel deep learning.
Aprile
21
2020
Francesco Vaccarino
On the geometry of learning
nel ciclo di seminari: GEOMETRIA E DEEP LEARNING
algebra e geometria
We will present and discuss the main geometric and topological approaches and results regarding Deep Neural Networks and Generative Adversarial Networks.
organizzato da: Rita Fioresi e Patrizio Frosini
Febbraio
11
2020
Rita Fioresi
A Geometric Interpretation of Stochastic Gradient Descent
nel ciclo di seminari: GEOMETRIA E DEEP LEARNING
algebra e geometria
We start with a review of the main steps of the Deep Learning algorithm, together with some historical remarks. We then concentrate on the key ingredient, stochastic gradient descent (SGD), whose geometric significance appears elusive and was modelled using the SDE Fokker Planck by Chaudhari and Soatto. We then study a deterministic model in which the trajectories of our dynamical systems are described via geodesics of a family of metrics arising from the diffusion matrix (natural gradient method). These metrics encode information about the highly non-isotropic gradient noise in SGD. This is a joint work with S. Soatto (UCLA, Amazon) and P. Chaudhari (U. Penn.)
organizzato da: Rita Fioresi e Patrizio Frosini