Regression based D-optimality experimental design for sparse kernel density estimation

Sheng Chen, Xia Hong, C.J. Harris

Type: Article

Publication Date: 2009-11-19

Citations: 11

DOI: https://doi.org/10.1016/j.neucom.2009.11.002

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ePrints Soton (University of Southampton) - View - PDF
Neurocomputing - View

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Works Cited by This (13)

Action	Title	Year	Authors
+	Applied Smoothing Techniques for Data Analysis	1999	Richard D. DeVeaux Adrian Bowman Adelchi Azzalini
+	Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm	1977	A. P. Dempster N. M. Laird Donald B. Rubin
+ PDF Chat	Robust maximum likelihood training of heteroscedastic probabilistic neural networks	1998	Zheng Rong Yang Sheng Chen
+ PDF Chat	Robust Bayesian clustering	2006	Cédric Archambeau Michel Verleysen
+	Cross-Validatory Choice and Assessment of Statistical Predictions	1974	M. Stone
+	A Forward-Constrained Regression Algorithm for Sparse Kernel Density Estimation	2008	Xia Hong Sheng Chen C.J. Harris
+	Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines	2002	Fei Sha Lawrence K. Saul Daniel D. Lee
+	Support Vector Method for Multivariate Density Estimation	1999	Vladimir Vapnik Sayan Mukherjee
+	Robust Bayesian mixture modelling	2005	Markus Svensén Chris Bishop
+	Sparse Modeling Using Orthogonal Forward Regression With PRESS Statistic and Regularization	2004	Sheng Chen Xia Hong C.J. Harris Paul Sharkey