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» On the Noise Model of Support Vector Machines Regression
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ICML
2004
IEEE
14 years 9 months ago
Improving SVM accuracy by training on auxiliary data sources
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Pengcheng Wu, Thomas G. Dietterich
BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
14 years 3 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy
IJCNN
2007
IEEE
14 years 3 months ago
On Extending the SMO Algorithm Sub-Problem
—The Support Vector Machine is a widely employed machine learning model due to its repeatedly demonstrated superior generalization performance. The Sequential Minimal Optimizatio...
Christopher Sentelle, Michael Georgiopoulos, Georg...
MIR
2006
ACM
195views Multimedia» more  MIR 2006»
14 years 2 months ago
Automatically selecting shots for action movie trailers
Movie trailers, or previews, are an important method of advertising movies. They are extensively shown before movies in cinemas, as well as on television and increasingly, over th...
Alan F. Smeaton, Bart Lehane, Noel E. O'Connor, Co...
COLT
2003
Springer
14 years 2 months ago
Maximum Margin Algorithms with Boolean Kernels
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
Roni Khardon, Rocco A. Servedio