Estimating Labels from Label Proportions Export

@article{citeulike:6089358, abstract = {Consider the following problem: given sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, possibly with known label proportions. This problem occurs in areas like e-commerce, politics, 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 = {Quadrianto, Novi and Smola, Alex J. and Caetano, Tib\'{e}rio S. and Le, Quoc V.}, citeulike-article-id = {6089358}, citeulike-linkout-0 = {http://www.jmlr.org/papers/volume10/quadrianto09a/quadrianto09a.pdf}, journal = {Journal of Machine Learning Research}, keywords = {lab}, month = {October}, pages = {2349--2374}, posted-at = {2009-11-09 16:50:24}, priority = {2}, title = {Estimating Labels from Label Proportions}, url = {http://www.jmlr.org/papers/volume10/quadrianto09a/quadrianto09a.pdf}, volume = {10}, year = {2009} }

TY - JOUR ID - citeulike:6089358 L3 - citeulike-article-id:6089358 N2 - Consider the following problem: given sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, possibly with known label proportions. This problem occurs in areas like e-commerce, politics, 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. JF - Journal of Machine Learning Research EP - 2374 TI - Estimating Labels from Label Proportions VL - 10 SP - 2349 KW - lab AU - Quadrianto, Novi AU - Smola, Alex AU - Caetano, Tibério AU - Le, Quoc PY - 2009/10// UR - http://www.jmlr.org/papers/volume10/quadrianto09a/quadrianto09a.pdf ER -