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» Algorithmic randomness of continuous functions
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JMLR
2010
137views more  JMLR 2010»
13 years 5 months 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
14 years 4 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
12 years 6 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
14 years 3 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
14 years 3 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