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.Full text not available from this repository.
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).
|Divisions:||Div F > Computational and Biological Learning|
|Depositing User:||Cron job|
|Date Deposited:||16 Jul 2015 13:06|
|Last Modified:||31 Jul 2015 03:53|