296 search results - page 6 / 60 » Extractive Summarization Using Supervised and Semi-Supervise... |
NIPS
2004
14 years 11 months ago
2004
We consider the situation in semi-supervised learning, where the "label sampling" mechanism stochastically depends on the true response (as well as potentially on the fe...
94
Voted
ACL
2008
14 years 11 months ago
2008
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
96
Voted
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...
80
Voted
AAAI
2007
15 years 22 hour ago
2007
In semi-supervised learning, a number of labeled examples are usually required for training an initial weakly useful predictor which is in turn used for exploiting the unlabeled e...
94
Voted
SDM
2008
SIAM
14 years 11 months ago
2008
SIAM
Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...