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» Learning from Multiple Sources of Inaccurate Data
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SIGIR
2006
ACM
14 years 2 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
ICML
2005
IEEE
14 years 9 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven
TNN
2008
178views more  TNN 2008»
13 years 8 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
NPL
2010
135views more  NPL 2010»
13 years 7 months ago
A Novel Regularization Learning for Single-View Patterns: Multi-View Discriminative Regularization
The existing Multi-View Learning (MVL) is to discuss how to learn from patterns with multiple information sources and has been proven its superior generalization to the usual Sing...
Zhe Wang, Songcan Chen, Hui Xue, Zhisong Pan
WWW
2008
ACM
14 years 9 months ago
Can chinese web pages be classified with english data source?
As the World Wide Web in China grows rapidly, mining knowledge in Chinese Web pages becomes more and more important. Mining Web information usually relies on the machine learning ...
Xiao Ling, Gui-Rong Xue, Wenyuan Dai, Yun Jiang, Q...