564 search results - page 26 / 113 » Approximation algorithms for restricted Bayesian network str... |
117
Voted
ICONIP
2007
15 years 2 months ago
2007
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
101
Voted
MTA
2010
14 years 11 months ago
2010
Abstract In this paper we propose a reduced-reference quality assessment algorithm which computes an approximation of the Structural SIMilarity (SSIM) metrics exploiting coding too...
UAI
2003
15 years 1 months ago
2003
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
87
Voted
ICPR
2008
IEEE
15 years 7 months ago
2008
IEEE
We propose a new method for recovering a 3-D object shape from an image sequence. In order to recover high-resolution relative depth without using the complex Markov random field...
HICSS
2007
IEEE
15 years 6 months ago
2007
IEEE
— Bayesian networks play a key role in decision support within health care. Physicians rely on Bayesian networks to give medical treatment, generate what-if scenarios, and other ...