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» Nonlinear functional regression: a functional RKHS approach
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JMLR
2010
110views more  JMLR 2010»
9 years 10 months ago
Nonlinear functional regression: a functional RKHS approach
This paper deals with functional regression, in which the input attributes as well as the response are functions. To deal with this problem, we develop a functional reproducing ke...
Hachem Kadri, Emmanuel Duflos, Philippe Preux, St&...
CVPR
2008
IEEE
11 years 6 months ago
Dimensionality reduction using covariance operator inverse regression
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
Minyoung Kim, Vladimir Pavlovic
FOCM
2007
76views more  FOCM 2007»
10 years 4 months ago
Risk Bounds for Random Regression Graphs
We consider the regression problem and describe an algorithm approximating the regression function by estimators piecewise constant on the elements of an adaptive partition. The pa...
Andrea Caponnetto, Steve Smale
ICML
2008
IEEE
11 years 4 months ago
An RKHS for multi-view learning and manifold co-regularization
Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing Kernel Hilbert Spaces (RKHSs)...
Vikas Sindhwani, David S. Rosenberg
JMLR
2010
130views more  JMLR 2010»
9 years 10 months ago
A Regularization Approach to Nonlinear Variable Selection
In this paper we consider a regularization approach to variable selection when the regression function depends nonlinearly on a few input variables. The proposed method is based o...
Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Ales...
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