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NIPS
1996
14 years 11 months ago
Radial Basis Function Networks and Complexity Regularization in Function Learning
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
Adam Krzyzak, Tamás Linder
TIT
2002
99views more  TIT 2002»
14 years 9 months ago
Poisson intensity estimation for tomographic data using a wavelet shrinkage approach
We consider a two-dimensional problem of positron emission tomography where the random mechanism of the generation of the tomographic data is modeled by Poisson processes. The goa...
L. Cavalier, Ja-Yong Koo
FLAIRS
2004
14 years 11 months ago
Multimodal Function Optimization Using Local Ruggedness Information
In multimodal function optimization, niching techniques create diversification within the population, thus encouraging heterogeneous convergence. The key to the effective diversif...
Jian Zhang 0007, Xiaohui Yuan, Bill P. Buckles
CSDA
2006
90views more  CSDA 2006»
14 years 10 months ago
Estimation in covariate-adjusted regression
Abstract: The method of covariate adjusted regression was recently proposed for situations where both predictors and response in a regression model are not directly observed, but a...
Damla Sentürk, Danh V. Nguyen
ML
2007
ACM
127views Machine Learning» more  ML 2007»
14 years 9 months ago
Density estimation with stagewise optimization of the empirical risk
We consider multivariate density estimation with identically distributed observations. We study a density estimator which is a convex combination of functions in a dictionary and ...
Jussi Klemelä