Seong Jin Cho

Proposes a new active learning approach by proposing a new uncertainty measure called the least disagree metric, as well as its efficient estimator, which is proven to be asymptotically consistent. This is then combined with seeding to become a new active learning algorith, LDM-S, which is shown to outperform existing approaches across various architectures and datasets.

Developed least disagree metric (LDM), a new disagreement-based uncertainty measure, and an LDM-based active learning algorithm with state-of-the-art performance guarantee.