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» Modeling Dependencies in Stochastic Simulation Inputs
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GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 10 months ago
ASAGA: an adaptive surrogate-assisted genetic algorithm
Genetic algorithms (GAs) used in complex optimization domains usually need to perform a large number of fitness function evaluations in order to get near-optimal solutions. In rea...
Liang Shi, Khaled Rasheed
INFOCOM
2005
IEEE
14 years 3 months ago
Spatial energy balancing in large-scale wireless multihop networks
— In this paper we investigate the use of proactive multipath routing to achieve energy efficient operation of ad hoc wireless networks. The focus is on optimizing trade-offs be...
Seung Jun Baek, Gustavo de Veciana
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 9 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
BPM
2011
Springer
270views Business» more  BPM 2011»
12 years 9 months ago
Automated Error Correction of Business Process Models
As order dependencies between process tasks can get complex, it is easy to make mistakes in process model design, especially behavioral ones such as deadlocks. Notions such as soun...
Mauro Gambini, Marcello La Rosa, Sara Migliorini, ...
IJCNN
2007
IEEE
14 years 4 months ago
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks
— A single biological neuron is able to perform complex computations that are highly nonlinear in nature, adaptive, and superior to the perceptron model. A neuron is essentially ...
Manish Saggar, Tekin Meriçli, Sari Andoni, ...