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IROS
2008
IEEE
211views Robotics» more  IROS 2008»
14 years 2 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
ICASSP
2009
IEEE
13 years 11 months ago
Dirichlet process mixture models with multiple modalities
The Dirichlet process can be used as a nonparametric prior for an infinite-dimensional probability mass function on the parameter space of a mixture model. The set of parameters o...
John William Paisley, Lawrence Carin
IFIP12
2009
13 years 5 months ago
An Expert System Based on Parametric Net to Support Motor Pump Multi-Failure Diagnostic
Abstract Early failure detection in motor pumps is an important issue in prediction maintenance. An efficient condition-monitoring scheme is capable of providing warning and predic...
Flavia Cristina Bernardini, Ana Cristina Bicharra ...
CSDA
2010
208views more  CSDA 2010»
13 years 7 months ago
Bayesian density estimation and model selection using nonparametric hierarchical mixtures
We consider mixtures of parametric densities on the positive reals with a normalized generalized gamma process (Brix, 1999) as mixing measure. This class of mixtures encompasses t...
Raffaele Argiento, Alessandra Guglielmi, Antonio P...
ICML
1998
IEEE
14 years 8 months ago
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
Moisés Goldszmidt, Nir Friedman, Thomas J. ...