3 papers
cs.LG2024
Learning the Target Network in Function Space
Kavosh Asadi, Yao Liu, Shoham Sabach +2
We focus on the task of learning the value function in the reinforcement learning (RL) setting. This task is often solved by updating a pair of online and target networks while ens…
cs.RO2024
EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data
Jesse Zhang, Minho Heo, Zuxin Liu +4
Most reinforcement learning (RL) methods focus on learning optimal policies over low-level action spaces. While these methods can perform well in their training environments, they…
cs.LG2024
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models
Zuxin Liu, Jesse Zhang, Kavosh Asadi +4
The full potential of large pretrained models remains largely untapped in control domains like robotics. This is mainly because of the scarcity of data and the computational challe…