28 citations · 33 across the 6 of their papers we have counts for
3 papers · 2 filters
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks
Fabian Latorre, Paul Rolland, Nadav Hallak +1
We demonstrate two new important properties of the 1-path-norm of shallow neural networks. First, despite its non-smoothness and non-convexity it allows a closed form proximal oper…
Lipschitz constant estimation of Neural Networks via sparse polynomial optimization
Fabian Latorre, Paul Rolland, Volkan Cevher
We introduce LiPopt, a polynomial optimization framework for computing increasingly tighter upper bounds on the Lipschitz constant of neural networks. The underlying optimization p…
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh +3
We introduce a sampling perspective to tackle the challenging task of training robust Reinforcement Learning (RL) agents. Leveraging the powerful Stochastic Gradient Langevin Dynam…