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» On Bayesian model and variable selection using MCMC
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FLAIRS
2004
14 years 11 months ago
An Empirical Study of Probability Elicitation Under Noisy-OR Assumption
Bayesian network is a popular modeling tool for uncertain domains that provides a compact representation of a joint probability distribution among a set of variables. Even though ...
Adam Zagorecki, Marek J. Druzdzel
ICML
2004
IEEE
15 years 10 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
HICSS
2010
IEEE
167views Biometrics» more  HICSS 2010»
15 years 4 months ago
Bayesian Networks for the Assessment of the Effect of Urbanization on Stream Macroinvertebrates
It is generally acknowledged that macroinvertebrates are good indicators of water quality in streams, as a number of taxa are sensitive to pollution and integrate their response t...
Kenneth H. Reckhow
NECO
2002
104views more  NECO 2002»
14 years 9 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
JAMDS
2002
107views more  JAMDS 2002»
14 years 9 months ago
Estimating a resource selection function with line transect sampling
Abstract. A resource selection probability function is a function that gives the probability that a resource unit (e.g., a plot of land) that is described by a set of habitat varia...
Bryan F. J. Manly