Estimating labels from label proportions
Novi Quadrianto, Alex Smola, Tiberio Caetano and quoc le
In: the 25th International Conference on Machine Learning, 05 July - 09 July 2008, Helsinki, Finland.
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.
|EPrint Type:||Conference or Workshop Item (Talk)|
|Additional Information:||Topics : Gaussian Processes, Classification and Prediction, Probabilistic Models, Transduction, Semi-supervised Learning|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Subjects:||Learning/Statistics & Optimisation|
|Deposited By:||Novi Quadrianto|
|Deposited On:||19 September 2008|