43 search results - page 1 / 9 » Expectation Maximization for Weakly Labeled Data |
ICML
2001
IEEE
14 years 5 months ago
2001
IEEE
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
JMLR
2010
12 years 11 months ago
2010
In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits m...
SDM
2011
SIAM
12 years 7 months ago
2011
SIAM
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
ICML
2001
IEEE
14 years 5 months ago
2001
IEEE
Data noise is present in many machine learning problems domains, some of these are well studied but others have received less attention. In this paper we propose an algorithm for ...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...