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» Algorithmic randomness of continuous functions
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JMLR
2010
137views more  JMLR 2010»
15 years 20 days ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
IPSN
2005
Springer
15 years 11 months ago
Robust computation of aggregates in wireless sensor networks: distributed randomized algorithms and analysis
A wireless sensor network consists of a large number of small, resource-constrained devices and usually operates in hostile environments that are prone to link and node failures. ...
Jen-Yeu Chen, Gopal Pandurangan, Dongyan Xu
SOCO
2012
Springer
14 years 1 months ago
Variable mesh optimization for continuous optimization problems
Abstract Population-based meta-heuristics are algorithms that can obtain very good results for complex continuous optimization problems in a reduced amount of time. These search al...
Amilkar Puris, Rafael Bello, Daniel Molina, Franci...
AE
2001
Springer
15 years 10 months ago
Markov Random Field Modelling of Royal Road Genetic Algorithms
Abstract. Markov Random Fields (MRFs) 5] are a class of probabalistic models that have been applied for many years to the analysis of visual patterns or textures. In this paper, ou...
Deryck F. Brown, A. Beatriz Garmendia-Doval, John ...
IJCNN
2000
IEEE
15 years 10 months ago
Analog Hardware Implementation of the Random Neural Network Model
This paper presents a simple continuous analog hardware realization of the Random Neural Network (RNN) model. The proposed circuit uses the general principles resulting from the u...
Hossam Abdelbaki, Erol Gelenbe, Said E. El-Khamy