Machine Learning Street Talk (MLST) cover image

CURL: Contrastive Unsupervised Representations for Reinforcement Learning

Machine Learning Street Talk (MLST)

00:00

Navigating Sample Efficiency Challenges in Reinforcement Learning

This chapter explores the sample efficiency problem in reinforcement learning, critiquing past research for neglecting direct comparisons between learning with raw features and pixel data. It also emphasizes the need for new benchmarks that promote faster learning and more efficient interactions in the field.

Transcript
Play full episode

The AI-powered Podcast Player

Save insights by tapping your headphones, chat with episodes, discover the best highlights - and more!
App store bannerPlay store banner
Get the app