206 search results - page 5 / 42 » Boosting Kernel Models for Regression |
ICANN
2003
Springer
14 years 9 days 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
13 years 8 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
13 years 7 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...
DAGM
2008
Springer
13 years 9 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
14 years 1 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...