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» Self-taught learning: transfer learning from unlabeled data
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NIPS
1998
13 years 9 months ago
Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
This paper presents probabilistic modeling methods to solve the problem of discriminating between five facial orientations with very little labeled data. Three models are explored...
Shumeet Baluja
BMCBI
2010
143views more  BMCBI 2010»
13 years 7 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
ML
2000
ACM
124views Machine Learning» more  ML 2000»
13 years 7 months ago
Text Classification from Labeled and Unlabeled Documents using EM
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. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
EMNLP
2010
13 years 5 months ago
Cross Language Text Classification by Model Translation and Semi-Supervised Learning
In this paper, we introduce a method that automatically builds text classifiers in a new language by training on already labeled data in another language. Our method transfers the...
Lei Shi, Rada Mihalcea, Mingjun Tian
AAAI
2008
13 years 10 months ago
Text Categorization with Knowledge Transfer from Heterogeneous Data Sources
Multi-category classification of short dialogues is a common task performed by humans. When assigning a question to an expert, a customer service operator tries to classify the cu...
Rakesh Gupta, Lev-Arie Ratinov