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» Bayesian Inference for Sparse Generalized Linear Models
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VLSID
2006
IEEE
129views VLSI» more  VLSID 2006»
16 years 2 months ago
A Stimulus-Free Probabilistic Model for Single-Event-Upset Sensitivity
With device size shrinking and fast rising frequency ranges, effect of cosmic radiations and alpha particles known as Single-Event-Upset (SEU), Single-Eventtransients (SET), is a ...
Mohammad Gh. Mohammad, Laila Terkawi, Muna Albasma...
ICDAR
2007
IEEE
15 years 8 months ago
A Shared Parts Model for Document Image Recognition
We address document image classification by visual appearance. An image is represented by a variable-length list of visually salient features. A hierarchical Bayesian network is ...
M. Das Gupta, P. Sarkar
AUTOMATICA
2006
63views more  AUTOMATICA 2006»
15 years 1 months ago
Inference of disjoint linear and nonlinear sub-domains of a nonlinear mapping
This paper investigates new ways of inferring nonlinear dependence from measured data. The existence of unique linear and nonlinear sub-spaces which are structural invariants of g...
Douglas J. Leith, William E. Leithead, Roderick Mu...
ECCV
2008
Springer
16 years 3 months ago
Online Sparse Matrix Gaussian Process Regression and Vision Applications
We present a new Gaussian Process inference algorithm, called Online Sparse Matrix Gaussian Processes (OSMGP), and demonstrate its merits with a few vision applications. The OSMGP ...
Ananth Ranganathan, Ming-Hsuan Yang
UAI
1997
15 years 3 months ago
Robustness Analysis of Bayesian Networks with Local Convex Sets of Distributions
Robust Bayesian inference is the calculation of posterior probability bounds given perturbations in a probabilistic model. This paper focuses on perturbations that can be expresse...
Fabio Gagliardi Cozman