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CORR
2012
Springer
214views Education» more  CORR 2012»
11 years 11 months ago
Stochastic Low-Rank Kernel Learning for Regression
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 ...
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandr...
ICCV
2011
IEEE
12 years 3 months ago
Regression from Local Features for Viewpoint and Pose Estimation
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...
Marwan Torki, Ahmed Elgammal
MA
2010
Springer
117views Communications» more  MA 2010»
13 years 2 months ago
Thresholding projection estimators in functional linear models
We consider the problem of estimating the regression function in functional linear regression models by proposing a new type of projection estimators which combine
Hervé Cardot, Jan Johannes
COLT
1997
Springer
13 years 7 months ago
Estimation of Time-Varying Parameters in Statistical Models: An Optimization Approach
Abstract. We propose a convex optimization approach to solving the nonparametric regression estimation problem when the underlying regression function is Lipschitz continuous. This...
Dimitris Bertsimas, David Gamarnik, John N. Tsitsi...