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» Income prediction via support vector machine
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TKDD
2008
113views more  TKDD 2008»
15 years 3 months ago
Privacy-preserving classification of vertically partitioned data via random kernels
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entiti...
Olvi L. Mangasarian, Edward W. Wild, Glenn Fung
111
Voted
IJDMB
2011
85views more  IJDMB 2011»
14 years 11 months ago
Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation
: Classification methods are vital for efficient access of knowledge hidden in biomedical publications. Support vector machines (SVMs) are modern non-parametric deterministic clas...
Tamara Polajnar, Simon Rogers, Mark Girolami
ICIP
2006
IEEE
16 years 5 months ago
Estimating Illumination Chromaticity via Kernel Regression
We propose a simple nonparametric linear regression tool, known as kernel regression (KR), to estimate the illumination chromaticity. We design a Gaussian kernel whose bandwidth i...
Vivek Agarwal, Andrei V. Gribok, Andreas Koschan, ...
123
Voted
ICASSP
2008
IEEE
15 years 10 months ago
Learning the kernel via convex optimization
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel it...
Seung-Jean Kim, Argyrios Zymnis, Alessandro Magnan...
117
Voted
SMC
2007
IEEE
113views Control Systems» more  SMC 2007»
15 years 10 months ago
Robust multi-modal biometric fusion via multiple SVMs
—Existing learning-based multi-modal biometric fusion techniques typically employ a single static Support Vector Machine (SVM). This type of fusion improves the accuracy of biome...
Sabra Dinerstein, Jonathan Dinerstein, Dan Ventura