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» Learning with Constrained and Unlabelled Data
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NIPS
2008
13 years 11 months ago
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
In this paper, we address the question of what kind of knowledge is generally transferable from unlabeled text. We suggest and analyze the semantic correlation of words as a gener...
Yi Zhang 0010, Jeff Schneider, Artur Dubrawski
ICML
2003
IEEE
14 years 11 months ago
Semi-Supervised Learning of Mixture Models
This paper analyzes the performance of semisupervised learning of mixture models. We show that unlabeled data can lead to an increase in classification error even in situations wh...
Fabio Gagliardi Cozman, Ira Cohen, Marcelo Cesar C...
ICPR
2008
IEEE
14 years 4 months ago
Semi-supervised discriminant analysis based on UDP regularization
We propose a semi-supervised learning algorithm for discriminant analysis, which uses the geometric structure of both labeled and unlabeled samples and perform a manifold regulari...
Huining Qiu, Jian-Huang Lai, Jian Huang, Yu Chen
SIGIR
2005
ACM
14 years 3 months ago
Automatic web query classification using labeled and unlabeled training data
Accurate topical categorization of user queries allows for increased effectiveness, efficiency, and revenue potential in general-purpose web search systems. Such categorization be...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...
CVPR
2008
IEEE
15 years 2 days ago
Semi-supervised boosting using visual similarity learning
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
Christian Leistner, Helmut Grabner, Horst Bischof