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JMLR
2011
148views more  JMLR 2011»
12 years 11 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
NECO
2007
129views more  NECO 2007»
13 years 4 months ago
Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...
Shinichi Nakajima, Sumio Watanabe
ICASSP
2009
IEEE
13 years 11 months ago
A mixed time-scale algorithm for distributed parameter estimation : Nonlinear observation models and imperfect communication
Abstract— The paper considers the algorithm NLU for distributed (vector) parameter estimation in sensor networks, where, the local observation models are nonlinear, and inter-sen...
Soummya Kar, José M. F. Moura
BMCBI
2008
159views more  BMCBI 2008»
13 years 4 months ago
Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via log
Background: Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that gen...
Dawei Liu, Debashis Ghosh, Xihong Lin
CSDA
2011
12 years 11 months ago
Improved interval estimation of long run response from a dynamic linear model: A highest density region approach
This paper proposes a new method of interval estimation for the long run response (or elasticity) parameter from a general linear dynamic model. We employ the biascorrected bootst...
Jae H. Kim, Iain Fraser, Rob J. Hyndman