239 search results - page 5 / 48 » Semi-supervised Learning from Unbalanced Labeled Data - An I... |
COLING
2008
13 years 9 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...
ICML
2010
IEEE
13 years 8 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
13 years 9 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...
ACL
2008
13 years 9 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...
CVPR
2006
IEEE
14 years 9 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...