Quadrianto, Novi and Smola, Alex and Caetano, Tiberio and Le, Quoc Viet
Consider the following problem: given several sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, also with known label proportions. This problem appears in areas like e-commerce, spam filtering, and improper content detection. We present consistent estimators which can reconstruct the correct labels with high probability in a uniform convergence sense. Experiments show that our method works well in practice.