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ICDM
2005
IEEE
165views Data Mining» more  ICDM 2005»
14 years 1 months ago
A Bernoulli Relational Model for Nonlinear Embedding
The notion of relations is extremely important in mathematics. In this paper, we use relations to describe the embedding problem and propose a novel stochastic relational model fo...
Gang Wang, Hui Zhang, Zhihua Zhang, Frederick H. L...
ICA
2007
Springer
13 years 11 months ago
Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
Ali Taylan Cemgil, Onur Dikmen
TSP
2008
179views more  TSP 2008»
13 years 7 months ago
Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis
Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fie...
V. Chandrasekaran, Jason K. Johnson, Alan S. Wills...
ICIP
2008
IEEE
14 years 9 months ago
Variational Bayesian image processing on stochastic factor graphs
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
Xin Li
ICPR
2004
IEEE
14 years 8 months ago
Joint Spatial and Temporal Structure Learning for Task based Control
We present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. We review work o...
Hilary Buxton, Kingsley Sage