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IJCAI
2007
13 years 9 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
ICML
2008
IEEE
14 years 8 months ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh
IVC
2000
186views more  IVC 2000»
13 years 7 months ago
Uncertainty analysis of 3D reconstruction from uncalibrated views
We consider reconstruction algorithms using points tracked over a sequence of (at least three) images, to estimate the positions of the cameras (motion parameters), the 3D coordin...
Etienne Grossmann, José Santos-Victor
ESANN
2003
13 years 9 months ago
On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures
Efficient probability density function estimation is of primary interest in statistics. A popular approach for achieving this is the use of finite Gaussian mixture models. Based on...
Cédric Archambeau, John Aldo Lee, Michel Ve...
UAI
2004
13 years 9 months ago
On Modeling Profiles Instead of Values
We consider the problem of estimating the distribution underlying an observed sample of data. Instead of maximum likelihood, which maximizes the probability of the observed values...
Alon Orlitsky, Narayana P. Santhanam, Krishnamurth...