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ICML
2005
IEEE
15 years 10 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...
MICCAI
2005
Springer
15 years 10 months ago
2005
Springer
Abstract. In this paper, we propose a new dynamic learning framework that requires a small amount of labeled data in the beginning, then incrementally discovers informative unlabel...
NIPS
2003
14 years 11 months ago
2003
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
AIRS
2006
Springer
15 years 1 months ago
2006
Springer
Many text documents naturally have two kinds of labels. For example, we may label web pages from universities according to their categories, such as "student" or "fa...
SAC
2004
ACM
15 years 2 months ago
2004
ACM
The importance of text mining stems from the availability of huge volumes of text databases holding a wealth of valuable information that needs to be mined. Text categorization is...