564 search results - page 6 / 113 » Approximation algorithms for restricted Bayesian network str... |
126
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ATAL
2003
Springer
15 years 10 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...
159
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AIIA
2003
Springer
15 years 10 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...
177
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ICANN
2010
Springer
15 years 5 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...
118
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IWINAC
2007
Springer
15 years 11 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 ...
142
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JCO
2011
14 years 11 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...