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» Approximate Learning of Dynamic Models
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JAIR
2008
113views more  JAIR 2008»
15 years 4 months ago
Graphical Model Inference in Optimal Control of Stochastic Multi-Agent Systems
In this article we consider the issue of optimal control in collaborative multi-agent systems with stochastic dynamics. The agents have a joint task in which they have to reach a ...
Bart van den Broek, Wim Wiegerinck, Bert Kappen
ICML
2007
IEEE
16 years 5 months ago
Hierarchical Gaussian process latent variable models
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Neil D. Lawrence, Andrew J. Moore
146
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JUCS
2007
107views more  JUCS 2007»
15 years 4 months ago
Genetic Algorithm Based Recurrent Fuzzy Neural Network Modeling of Chemical Processes
: A genetic algorithm (GA) based recurrent fuzzy neural network modeling method for dynamic nonlinear chemical process is presented. The dynamic recurrent fuzzy neural network (RFN...
Jili Tao, Ning Wang, Xuejun Wang
IJCSA
2007
110views more  IJCSA 2007»
15 years 4 months ago
Multiprocessor Scheduling Using Hybrid Particle Swarm Optimization with Dynamically Varying Inertia
The problem of task assignment in heterogeneous computing systems has been studied for many years with many variations. We have developed a new hybrid approximation algorithm. The...
S. N. Sivanandam, P. Visalakshi, A. Bhuvaneswari
IDA
2002
Springer
15 years 4 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer