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» Sparse Kernel Regressors
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RECOMB
2005
Springer
14 years 7 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
ICIP
2008
IEEE
14 years 9 months ago
Learning structurally discriminant features in 3D faces
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
ICPR
2004
IEEE
14 years 8 months ago
Localization of Saliency through Iterative Voting
Saliency is an important perceptual cue that occurs at different scales of resolution. Important attributes of saliency are symmetry, continuity, and closure. Detection of these a...
Bahram Parvin, Mary Helen Barcellos-Hoff, Qing Yan...
NIPS
2008
13 years 8 months ago
Theory of matching pursuit
We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound...
Zakria Hussain, John Shawe-Taylor
JCP
2006
102views more  JCP 2006»
13 years 7 months ago
Efficient Formulations for 1-SVM and their Application to Recommendation Tasks
The present paper proposes new approaches for recommendation tasks based on one-class support vector machines (1-SVMs) with graph kernels generated from a Laplacian matrix. We intr...
Yasutoshi Yajima, Tien-Fang Kuo