239 search results - page 5 / 48 » Semi-supervised Learning from Unbalanced Labeled Data - An I... |
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COLING
2008
14 years 11 months ago
2008
This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...
96
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ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
FLAIRS
2004
14 years 11 months ago
2004
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
100
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ACL
2008
14 years 11 months ago
2008
This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accompli...
100
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CVPR
2006
IEEE
15 years 11 months ago
2006
IEEE
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...