206 search results - page 5 / 42 » Boosting Kernel Models for Regression |
ICANN
2003
Springer
15 years 3 months ago
2003
Springer
Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
ESANN
2004
14 years 11 months ago
2004
In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based MacKay's evidence approximation. The model is re-p...
CSDA
2007
14 years 9 months ago
2007
Ridge regression is a well established method to shrink regression parameters towards zero, thereby securing existence of estimates. The present paper investigates several approac...
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DAGM
2008
Springer
14 years 11 months ago
2008
Springer
Abstract. This paper proposes a regression-based method for singleimage super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underl...
IJCNN
2007
IEEE
15 years 4 months ago
2007
IEEE
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...