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» Bayesian Parameter Estimation: A Monte Carlo Approach
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ICML
2005
IEEE
14 years 8 months ago
Dirichlet enhanced relational learning
We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be "personalized", i.e., owned b...
Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Pe...
CSDA
2006
117views more  CSDA 2006»
13 years 7 months ago
Exact maximum likelihood estimation of structured or unit root multivariate time series models
TheexactlikelihoodfunctionofaGaussianvectorautoregressive-movingaverage(VARMA)model is evaluated in two nonstandard cases: (a) a parsimonious structured form, such as obtained in ...
Guy Mélard, Roch Roy, Abdessamad Saidi
WSC
1997
13 years 8 months ago
Weighted Jackknife-after-Bootstrap: A Heuristic Approach
We investigate the problem of deriving precision estimates for bootstrap quantities. The one major stipulation is that no further bootstrapping will be allowed. In 1992, Efron der...
Jin Wang, J. Sunil Rao, Jun Shao
UAI
2001
13 years 8 months ago
Improved learning of Bayesian networks
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...
Tomás Kocka, Robert Castelo
CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Marked Point Processes for Crowd Counting
A Bayesian marked point process (MPP) model is developed to detect and count people in crowded scenes. The model couples a spatial stochastic process governing number and placem...
Robert T. Collins, Weina Ge