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NIPS
1998
14 years 11 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
BLISS
2009
IEEE
14 years 11 months ago
Gait Recognition Using Shadow Analysis
The exploitation of biometrics information in human shadow silhouettes (shadow biometrics), derived from video imagery after processing by gait analysis methods opens new avenues ...
Yumi Iwashita, Adrian Stoica
BMCBI
2010
146views more  BMCBI 2010»
14 years 10 months ago
Nonnegative principal component analysis for mass spectral serum profiles and biomarker discovery
Background: As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. Ho...
Henry Han
BMCBI
2007
140views more  BMCBI 2007»
14 years 10 months ago
Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets
Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles...
Michael Gormley, William Dampier, Adam Ertel, Bilg...
BMCBI
2007
178views more  BMCBI 2007»
14 years 10 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat