143 citations · 285 across the 7 of their papers we have counts for
3 papers · 1 filter
Neural Regression For Scale-Varying Targets
Adam Khakhar, Jacob Buckman
In this work, we demonstrate that a major limitation of regression using a mean-squared error loss is its sensitivity to the scale of its targets. This makes learning settings cons…
When does return-conditioned supervised learning work for offline reinforcement learning?
David Brandfonbrener, Alberto Bietti, Jacob Buckman +2
Several recent works have proposed a class of algorithms for the offline reinforcement learning (RL) problem that we will refer to as return-conditioned supervised learning (RCSL).…
Non-Markovian policies occupancy measures
Romain Laroche, Remi Tachet des Combes, Jacob Buckman
A central object of study in Reinforcement Learning (RL) is the Markovian policy, in which an agent's actions are chosen from a memoryless probability distribution, conditioned onl…