  This paper proposes a novel and efficient method for Learning from Label
Proportions (LLP), whose goal is to train a classifier only by using the class
label proportions of instance sets, called bags. We propose a novel LLP method
based on an online pseudo-labeling method with regret minimization. As opposed
to the previous LLP methods, the proposed method effectively works even if the
bag sizes are large. We demonstrate the effectiveness of the proposed method
using some benchmark datasets.
