125 search results - page 4 / 25 » Combining labeled and unlabeled data with word-class distrib... |
103
Voted
ICDM
2003
IEEE
15 years 2 months ago
2003
IEEE
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
ML
2000
ACM
14 years 9 months ago
2000
ACM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
ICDM
2003
IEEE
15 years 2 months ago
2003
IEEE
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
89
Voted
ECML
2004
Springer
15 years 3 months ago
2004
Springer
Abstract. In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image ret...
105
click to vote
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...