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AMC
2007
154views more  AMC 2007»
15 years 4 months ago
A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
The particle swarm optimization algorithm was showed to converge rapidly during the initial stages of a global search, but around global optimum, the search process will become ve...
Jing-Ru Zhang, Jun Zhang, Tat-Ming Lok, Michael R....
132
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MA
2010
Springer
172views Communications» more  MA 2010»
15 years 2 months ago
On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors
We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such models are used to analy...
Vivekananda Roy, James P. Hobert
NIPS
1998
15 years 5 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
INFOCOM
2007
IEEE
15 years 10 months ago
Iterative Scheduling Algorithms
— The input-queued switch architecture is widely used in Internet routers due to its ability to run at very high line speeds. A central problem in designing an input-queued switc...
Mohsen Bayati, Balaji Prabhakar, Devavrat Shah, Ma...
IWANN
2001
Springer
15 years 8 months ago
A New Approach to Evolutionary Computation: Segregative Genetic Algorithms (SEGA)
This paper looks upon the standard genetic algorithm as an artificial self-organizing process. With the purpose to provide concepts that make the algorithm more open for scalabili...
Michael Affenzeller