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JMLR
2002
106views more  JMLR 2002»
13 years 7 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
CVPR
2008
IEEE
14 years 9 months ago
Dimensionality reduction by unsupervised regression
We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
Miguel Á. Carreira-Perpiñán, ...
ICIC
2007
Springer
14 years 1 months ago
A Sparse Kernel Density Estimation Algorithm Using Forward Constrained Regression
Abstract. Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward constrained regression manner. The...
Xia Hong, Sheng Chen, Chris Harris
FSS
2006
102views more  FSS 2006»
13 years 7 months ago
Consistent Sobolev regression via fuzzy systems with overlapping concepts
In this paper we propose a new nonparametric regression algorithm based on Fuzzy systems with overlapping concepts. We analyze its consistency properties, showing that it is capab...
Giancarlo Ferrari-Trecate, Riccardo Rovatti
GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
13 years 11 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon