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» Evaluating learning algorithms and classifiers
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COLING
2008
13 years 12 months ago
A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations
Recognizing analogies, synonyms, antonyms, and associations appear to be four distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks have been treated inde...
Peter D. Turney
ICMLA
2010
13 years 8 months ago
Smoothing Gene Expression Using Biological Networks
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
CVPR
2009
IEEE
15 years 5 months ago
Learning a Distance Metric from Multi-instance Multi-label Data
Multi-instance multi-label learning (MIML) refers to the learning problems where each example is represented by a bag/collection of instances and is labeled by multiple labels. ...
Rong Jin (Michigan State University), Shijun Wang...
JMLR
2010
140views more  JMLR 2010»
13 years 5 months ago
Learning From Crowds
For many supervised learning tasks it may be infeasible (or very expensive) to obtain objective and reliable labels. Instead, we can collect subjective (possibly noisy) labels fro...
Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Gerard...
ICANN
2009
Springer
14 years 2 months ago
Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning
This paper proposes a novel Mass Spectrometry data profiling method for ovarian cancer detection based on negative correlation learning (NCL). A modified Smoothed Nonlinear Energy ...
Shan He, Huanhuan Chen, Xiaoli Li, Xin Yao