Kristen Goebel

Budgeted Online Active Learning with Expert Advice and Episodic Priors

This paper introduces a novel approach to budgeted online active learning from finite-horizon data streams with extremely limited labeling budgets. In agricultural applications, such streams might include daily weather data over a growing season, and labels require costly measurements of weather-dep