2.3k citations · 3.2k across the 54 of their papers we have counts for
60 papers
Improving Policy Learning from Delayed Interventions
Xiru Zhu, David Meger, Gregory Dudek
In this work, we explore the idea of expert intervention delays in human-supervised robotic systems for imitation learning system. Previous works in imitation learning have primari…
Convergence Theorems for Entropy-Regularized and Distributional Reinforcement Learning
Yash Jhaveri, Harley Wiltzer, Patrick Shafto +2
In the pursuit of finding an optimal policy, reinforcement learning (RL) methods generally ignore the properties of learned policies apart from their expected return. Thus, even wh…
Large Pre-Trained Models for Bimanual Manipulation in 3D
Hanna Yurchyk, Wei-Di Chang, Gregory Dudek +1
We investigate the integration of attention maps from a pre-trained Vision Transformer into voxel representations to enhance bimanual robotic manipulation. Specifically, we extract…
EMoE: Training-Free Expert Disagreement for Uncertainty-Aware Text-to-Image Diffusion
Lucas Berry, Axel Brando, Wei-Di Chang +2
Large text-to-image diffusion models rarely expose reliable signals of when a prompt is likely to produce a poorly aligned generation, especially when training data is undisclosed.…
Tractable Representations for Convergent Approximation of Distributional HJB Equations
Julie Alhosh, Harley Wiltzer, David Meger
In reinforcement learning (RL), the long-term behavior of decision-making policies is evaluated based on their average returns. Distributional RL has emerged, presenting techniques…
Fairness in Reinforcement Learning with Bisimulation Metrics
Sahand Rezaei-Shoshtari, Hanna Yurchyk, Scott Fujimoto +2
Ensuring long-term fairness is crucial when developing automated decision making systems, specifically in dynamic and sequential environments. By maximizing their reward without co…