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» On Nonparametric Residual Variance Estimation
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CAIP
2005
Springer
133views Image Analysis» more  CAIP 2005»
14 years 18 days ago
Finding the Number of Clusters for Nonparametric Segmentation
Non-parametric data representation can be done by means of a potential function. This paper introduces a methodology for finding modes of the potential function. Two different me...
Nikolaos Nasios, Adrian G. Bors
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
14 years 21 hour ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
IJON
1998
44views more  IJON 1998»
13 years 6 months ago
Hierarchical RBF networks and local parameters estimate
The method presented here is aimed to a direct fast setting of the parameters of a RBF network for function approximation. It is based on a hierarchical gridding of the input spac...
N. Alberto Borghese, Stefano Ferrari
BMCBI
2006
151views more  BMCBI 2006»
13 years 7 months ago
Modeling Sage data with a truncated gamma-Poisson model
Background: Serial Analysis of Gene Expressions (SAGE) produces gene expression measurements on a discrete scale, due to the finite number of molecules in the sample. This means t...
Helene H. Thygesen, Aeilko H. Zwinderman
ML
2007
ACM
127views Machine Learning» more  ML 2007»
13 years 6 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