@inproceedings{528fb92efc2c4a028b5bfb2eca91812a,
title = "Estimating labels from label proportions",
abstract = "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.",
author = "Novi Quadrianto and Smola, {Alex J.} and Caetano, {Tiberio S.} and Le, {Quoc V.}",
year = "2008",
doi = "10.1145/1390156.1390254",
language = "English",
isbn = "9781605582054",
series = "Proceedings of the 25th International Conference on Machine Learning",
publisher = "Association for Computing Machinery (ACM)",
pages = "776--783",
booktitle = "Proceedings of the 25th International Conference on Machine Learning",
address = "United States",
note = "25th International Conference on Machine Learning ; Conference date: 05-07-2008 Through 09-07-2008",
}