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» Exploiting unlabeled data in ensemble methods
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SIGKDD
2008
150views more  SIGKDD 2008»
13 years 5 months ago
Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method
This paper presents our solution for KDD Cup 2008 competition that aims at optimizing the area under ROC for breast cancer detection. We exploited weighted-based classification me...
Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Ch...
JMLR
2006
186views more  JMLR 2006»
13 years 5 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
CVPR
2008
IEEE
14 years 7 months 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
PAKDD
2009
ACM
151views Data Mining» more  PAKDD 2009»
14 years 6 days ago
Budget Semi-supervised Learning
In this paper we propose to study budget semi-supervised learning, i.e., semi-supervised learning with a resource budget, such as a limited memory insufficient to accommodate and/...
Zhi-Hua Zhou, Michael Ng, Qiao-Qiao She, Yuan Jian...
PRIB
2009
Springer
187views Bioinformatics» more  PRIB 2009»
13 years 10 months ago
Semi-supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics
Protein-protein interaction (PPI) identification is an integral component of many biomedical research and database curation tools. Automation of this task through classification ...
Tamara Polajnar, Mark A. Girolami