Estimating labels from label proportions

Consider the following problem: given 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.

• Type: Conference
• Year: 2008
• Where: ICML
• Authors: Alex J. Smola, Novi Quadrianto, Quoc V. Le, Tibério S. Caetano
• Keywords: ICML 2008, Improper Content Detection, Label Proportions, Machine Learning, Uniform Convergence Sense