PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Estimating Labels from Label Proportions
Novi Quadrianto, Alex J. Smola, Tiberio S. Caetano and Quoc V. Le
In: ICML 2008, Helsinki(2008).

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 ltering 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.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:5273
Deposited By:Tiberio Caetano
Deposited On:24 March 2009