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» Boosting Kernel Models for Regression
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FGR
2006
IEEE
108views Biometrics» more  FGR 2006»
15 years 1 months ago
Regression and Classification Approaches to Eye Localization in Face Images
We address the task of accurately localizing the eyes in face images extracted by a face detector, an important problem to be solved because of the negative effect of poor localiz...
Mark Everingham, Andrew Zisserman
BMCBI
2010
150views more  BMCBI 2010»
14 years 7 months ago
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
PAMI
2010
337views more  PAMI 2010»
14 years 8 months ago
Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior
—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...
Kwang In Kim, Younghee Kwon
ICML
2007
IEEE
15 years 10 months ago
Kernelizing PLS, degrees of freedom, and efficient model selection
Kernelizing partial least squares (PLS), an algorithm which has been particularly popular in chemometrics, leads to kernel PLS which has several interesting properties, including ...
Mikio L. Braun, Nicole Krämer
ICML
2006
IEEE
15 years 10 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil