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» Arguing from Experience to Classifying Noisy Data
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ICML
2003
IEEE
14 years 9 months ago
Learning with Knowledge from Multiple Experts
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
Matthew Richardson, Pedro Domingos
NIPS
2008
13 years 10 months ago
Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance
From an information-theoretic perspective, a noisy transmission system such as a visual Brain-Computer Interface (BCI) speller could benefit from the use of errorcorrecting codes....
N. Jeremy Hill, Jason Farquhar, Suzanna Martens, F...
RECOMB
2003
Springer
14 years 9 months ago
Joint classifier and feature optimization for cancer diagnosis using gene expression data
Recent research has demonstrated quite convincingly that accurate cancer diagnosis can be achieved by constructing classifiers that are designed to compare the gene expression pro...
Balaji Krishnapuram, Lawrence Carin, Alexander J. ...
AIRWEB
2009
Springer
14 years 3 months ago
Looking into the past to better classify web spam
Web spamming techniques aim to achieve undeserved rankings in search results. Research has been widely conducted on identifying such spam and neutralizing its influence. However,...
Na Dai, Brian D. Davison, Xiaoguang Qi
MICAI
2010
Springer
13 years 7 months ago
Combining Neural Networks Based on Dempster-Shafer Theory for Classifying Data with Imperfect Labels
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
Mahdi Tabassian, Reza Ghaderi, Reza Ebrahimpour