Speaker
Balint Daroczy
(HUN-REN SZTAKI)
Description
We consider generalization bounds for two types of neural structures, feedforward Rectified Linear Unit (ReLU) networks, special types of neural Ordinary Differential Equations (ODE) and State Space Models (SSM). Calculating the Rademacher complexity of both models involves computationally expensive norm calculations therefore we propose techniques to compute them efficiently.
Primary author
Balint Daroczy
(HUN-REN SZTAKI)
