research
∙
09/22/2022
Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning
While Reinforcement Learning (RL) aims to train an agent from a reward f...
share
research
∙
03/08/2022
Score matching enables causal discovery of nonlinear additive noise models
This paper demonstrates how to recover causal graphs from the score of t...
research
∙
07/02/2020
Double-Loop Unadjusted Langevin Algorithm
A well-known first-order method for sampling from log-concave probabilit...
research
∙
07/02/2020
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks
We demonstrate two new important properties of the 1-path-norm of shallo...
research
∙
04/18/2020
Lipschitz constant estimation of Neural Networks via sparse polynomial optimization
We introduce LiPopt, a polynomial optimization framework for computing i...
research
∙
02/14/2020
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
We introduce a sampling perspective to tackle the challenging task of tr...
research
∙
12/11/2018
Efficient learning of smooth probability functions from Bernoulli tests with guarantees
We study the fundamental problem of learning an unknown, smooth probabil...
research
∙
02/20/2018