CUED Publications database

Estimating labels from label proportions

Quadrianto, N and Smola, AJ and Caetano, TS and Le, QV (2008) Estimating labels from label proportions. Proceedings of the 25th International Conference on Machine Learning. pp. 776-783.

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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. Copyright 2008 by the author(s)/owner(s).

Item Type: Article
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:23
Last Modified: 17 Apr 2018 03:13