2 papers
cs.LG2025
Accelerated Online Reinforcement Learning using Auxiliary Start State Distributions
Aman Mehra, Alexandre Capone, Jeff Schneider
A long-standing problem in online reinforcement learning (RL) is of ensuring sample efficiency, which stems from an inability to explore environments efficiently. Most attempts at…
cs.LG2024
Predicting the Performance of Foundation Models via Agreement-on-the-Line
Rahul Saxena, Taeyoun Kim, Aman Mehra +3
Estimating the out-of-distribution performance in regimes where labels are scarce is critical to safely deploy foundation models. Recently, it was shown that ensembles of neural ne…