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ICASSP
2009
IEEE
14 years 1 months ago
Principal component analysis in decomposable Gaussian graphical models
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
Ami Wiesel, Alfred O. Hero III
CSDA
2010
118views more  CSDA 2010»
13 years 10 months ago
Grapham: Graphical models with adaptive random walk Metropolis algorithms
Recently developed adaptive Markov chain Monte Carlo (MCMC) methods have been applied successfully to many problems in Bayesian statistics. Grapham is a new open source implementat...
Matti Vihola
SCA
2007
14 years 11 days ago
Harmonic skeleton for realistic character animation
Current approaches to skeleton generation are based on topological and geometrical information only; this can be insufficient for realistic character animation, since the location...
Grégoire Aujay, Franck Hétroy, Franc...
UAI
2008
13 years 11 months ago
Adaptive inference on general graphical models
Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform upd...
Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mett...
UAI
2004
13 years 11 months ago
A Hierarchical Graphical Model for Record Linkage
The task of matching co-referent records is known among other names as record linkage. For large record-linkage problems, often there is little or no labeled data available, but u...
Pradeep D. Ravikumar, William W. Cohen