CORR
2012
Springer
12 years 9 months ago
2012
Springer
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
ICCV
2011
IEEE
13 years 1 months ago
2011
IEEE
In this paper we propose a framework for learning a regression function form a set of local features in an image. The regression is learned from an embedded representation that re...
MA
2010
Springer
14 years 6 days ago
2010
Springer
We consider the problem of estimating the regression function in functional linear regression models by proposing a new type of projection estimators which combine
COLT
1997
Springer
14 years 6 months ago
1997
Springer
Abstract. We propose a convex optimization approach to solving the nonparametric regression estimation problem when the underlying regression function is Lipschitz continuous. This...