1 citations · 1 across the 3 of their papers we have counts for
3 papers
Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials
Aviral Kumar, Anikait Singh, Frederik Ebert +4
Progress in deep learning highlights the tremendous potential of utilizing diverse robotic datasets for attaining effective generalization and makes it enticing to consider leverag…
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets
Frederik Ebert, Yanlai Yang, Karl Schmeckpeper +5
Robot learning holds the promise of learning policies that generalize broadly. However, such generalization requires sufficiently diverse datasets of the task of interest, which ca…
Garbage In, Garbage Out? Do Machine Learning Application Papers in Social Computing Report Where Human-Labeled Training Data Comes From?
R. Stuart Geiger, Kevin Yu, Yanlai Yang +4
Many machine learning projects for new application areas involve teams of humans who label data for a particular purpose, from hiring crowdworkers to the paper's authors labeling t…