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» Learning from Ambiguously Labeled Examples
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BMCBI
2010
143views more  BMCBI 2010»
13 years 11 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
ICDM
2009
IEEE
130views Data Mining» more  ICDM 2009»
14 years 5 months ago
Active Learning with Generalized Queries
—Active learning can actively select or construct examples to label to reduce the number of labeled examples needed for building accurate classifiers. However, previous works of...
Jun Du, Charles X. Ling
CIVR
2006
Springer
186views Image Analysis» more  CIVR 2006»
14 years 2 months ago
Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
CVPR
2005
IEEE
15 years 28 days ago
Pruning Training Sets for Learning of Object Categories
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...
Anelia Angelova, Yaser S. Abu-Mostafa, Pietro Pero...
CVPR
2010
IEEE
14 years 7 months ago
Learning to Recognize Shadows in Monochromatic Natural Images
This paper addresses the problem of recognizing shadows from monochromatic natural images. Without chromatic information, shadow classification is very challenging because the in...
Jiejie Zhu, Kegan Samuel, Syed Zain Masood, Marsha...