564 search results - page 6 / 113 » Approximation algorithms for restricted Bayesian network str... |
ATAL
2003
Springer
14 years 1 months ago
2003
Springer
In complex distributed applications, a problem is often decomposed into a set of subproblems that are distributed to multiple agents. We formulate this class of problems with a tw...
AIIA
2003
Springer
14 years 1 months ago
2003
Springer
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
ICANN
2010
Springer
13 years 9 months ago
2010
Springer
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
IWINAC
2007
Springer
14 years 2 months ago
2007
Springer
One of the key points in Estimation of Distribution Algorithms (EDAs) is the learning of the probabilistic graphical model used to guide the search: the richer the model the more ...
JCO
2011
13 years 3 months ago
2011
Discrete gate sizing is a critical optimization in VLSI circuit design. Given a set of available gate sizes, discrete gate sizing problem asks to assign a size to each gate such th...