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SIMPRA
2008
125views more  SIMPRA 2008»
15 years 2 months ago
Identification of Wiener models using optimal local linear models
The Wiener model is a versatile nonlinear block oriented model structure for miscellaneous applications. In this paper a method for identifying the parameters of such a model usin...
Martin Kozek, Sabina Sinanovic
CVPR
2005
IEEE
16 years 5 months ago
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin
138
Voted
PE
2010
Springer
170views Optimization» more  PE 2010»
15 years 1 months ago
Approximating passage time distributions in queueing models by Bayesian expansion
We introduce Bayesian Expansion (BE), an approximate numerical technique for passage time distribution analysis in queueing networks. BE uses a class of Bayesian networks to appro...
Giuliano Casale
TSP
2010
14 years 9 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...
ICASSP
2009
IEEE
15 years 9 months ago
Decentralized variational filtering for simultaneous sensor localization and target tracking in binary sensor networks
Resource limitations in wireless sensor networks have put stringent constraints on distributed signal processing. In this paper, we propose a cluster-based decentralized variation...
Jing Teng, Hichem Snoussi, Cédric Richard