CORR
2012
Springer
12 years 8 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 13 days 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
13 years 11 months 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 4 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...