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ICPR
2002
IEEE
16 years 4 months ago
Bayesian Rendering with Non-Parametric Multiscale Prior Model
This paper investigates the use of the Bayesian inference for devising an example-based rendering procedure. As prior model of this Bayesian inference, we exploit the multiscale n...
Max Mignotte
CORR
2010
Springer
171views Education» more  CORR 2010»
15 years 3 months ago
Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
Guoshen Yu, Guillermo Sapiro, Stéphane Mall...
JMLR
2000
134views more  JMLR 2000»
15 years 3 months ago
Learning with Mixtures of Trees
This paper describes the mixtures-of-trees model, a probabilistic model for discrete multidimensional domains. Mixtures-of-trees generalize the probabilistic trees of Chow and Liu...
Marina Meila, Michael I. Jordan
PAMI
2010
113views more  PAMI 2010»
15 years 2 months ago
Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents
—We consider the problem of inferring and modeling topics in a sequence of documents with known publication dates. The documents at a given time are each characterized by a topic...
Iulian Pruteanu-Malinici, Lu Ren, John William Pai...
SUM
2009
Springer
15 years 10 months ago
Modeling Unreliable Observations in Bayesian Networks by Credal Networks
Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
Alessandro Antonucci, Alberto Piatti