18 citations · 29 across the 2 of their papers we have counts for
4 papers
Generalized Hindsight for Reinforcement Learning
Alexander C. Li, Lerrel Pinto, Pieter Abbeel
One of the key reasons for the high sample complexity in reinforcement learning (RL) is the inability to transfer knowledge from one task to another. In standard multi-task RL sett…
Autoregressive Models: What Are They Good For?
Murtaza Dalal, Alexander C. Li, Rohan Taori
Autoregressive (AR) models have become a popular tool for unsupervised learning, achieving state-of-the-art log likelihood estimates. We investigate the use of AR models as density…
Sub-policy Adaptation for Hierarchical Reinforcement Learning
Alexander C. Li, Carlos Florensa, Ignasi Clavera +1
Hierarchical reinforcement learning is a promising approach to tackle long-horizon decision-making problems with sparse rewards. Unfortunately, most methods still decouple the lowe…
Generative Models for Pose Transfer
Patrick Chao, Alexander Li, Gokul Swamy
We investigate nearest neighbor and generative models for transferring pose between persons. We take in a video of one person performing a sequence of actions and attempt to genera…