The core challenge of offline reinforcement learning (RL) is dealing wit...
Despite the seeming success of contemporary grounded text generation sys...
We consider the Imitation Learning (IL) setup where expert data are not
...
Energy-based models, a.k.a. energy networks, perform inference by optimi...
In Reinforcement Learning (RL), discrete actions, as opposed to continuo...
Offline Reinforcement Learning (RL) aims at learning an optimal control ...
Adversarial imitation learning has become a popular framework for imitat...
We address the issue of tuning hyperparameters (HPs) for imitation learn...
Offline Reinforcement Learning methods seek to learn a policy from logge...
The study of exploration in Reinforcement Learning (RL) has a long histo...
Imitation Learning (IL) methods seek to match the behavior of an agent w...
We present a unifying framework for designing and analysing distribution...
This paper proposes a new approach to representation learning based on
g...
We establish geometric and topological properties of the space of value
...
A key factor in developing high performing machine learning models is th...