35 citations · 64 across the 6 of their papers we have counts for
9 papers
Offline RL With Realistic Datasets: Heteroskedasticity and Support Constraints
Anikait Singh, Aviral Kumar, Quan Vuong +2
Offline reinforcement learning (RL) learns policies entirely from static datasets, thereby avoiding the challenges associated with online data collection. Practical applications of…
Dual Generator Offline Reinforcement Learning
Quan Vuong, Aviral Kumar, Sergey Levine +1
In offline RL, constraining the learned policy to remain close to the data is essential to prevent the policy from outputting out-of-distribution (OOD) actions with erroneously ove…
Single RGB-D Camera Teleoperation for General Robotic Manipulation
Quan Vuong, Yuzhe Qin, Runlin Guo +3
We propose a teleoperation system that uses a single RGB-D camera as the human motion capture device. Our system can perform general manipulation tasks such as cloth folding, hamme…
Machine Learning for Robotic Manipulation
Quan Vuong
The past decade has witnessed the tremendous successes of machine learning techniques in the supervised learning paradigm, where there is a clear demarcation between training and t…
First Order Constrained Optimization in Policy Space
Yiming Zhang, Quan Vuong, Keith W. Ross
In reinforcement learning, an agent attempts to learn high-performing behaviors through interacting with the environment, such behaviors are often quantified in the form of a rewar…
Better Exploration with Optimistic Actor-Critic
Kamil Ciosek, Quan Vuong, Robert Loftin +1
Actor-critic methods, a type of model-free Reinforcement Learning, have been successfully applied to challenging tasks in continuous control, often achieving state-of-the art perfo…