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» Kernel Logistic Regression and the Import Vector Machine
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ICASSP
2008
IEEE
15 years 6 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...
MICCAI
2008
Springer
16 years 26 days ago
Analysis of Surfaces Using Constrained Regression Models
We present a study of the relationship between the changes in the shape of the human ear due to jaw movement and acoustical feedback (AF) in hearing aids. In particular, we analyze...
Sune Darkner, Mert R. Sabuncu, Polina Golland, ...
MLDM
2007
Springer
15 years 5 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
NIPS
2001
15 years 1 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
ICCV
2009
IEEE
16 years 4 months ago
Heterogeneous Feature Machines for Visual Recognition
With the recent efforts made by computer vision researchers, more and more types of features have been designed to describe various aspects of visual characteristics. Modeling s...
Liangliang Cao, Jiebo Luo, Feng Liang, Thomas S. H...