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ICML
2004
IEEE
14 years 8 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
ARTMED
1999
92views more  ARTMED 1999»
13 years 7 months ago
Two-Stage Machine Learning model for guideline development
We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clin...
Subramani Mani, William Rodman Shankle, Malcolm B....
NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 7 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
CVPR
2006
IEEE
14 years 1 months ago
Learning Non-Metric Partial Similarity Based on Maximal Margin Criterion
The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...
Xiaoyang Tan, Songcan Chen, Jun Li, Zhi-Hua Zhou
CVPR
2006
IEEE
14 years 9 months ago
Joint Boosting Feature Selection for Robust Face Recognition
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framewo...
Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang