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» Using Gaussian Processes to Optimize Expensive Functions
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CEC
2005
IEEE
13 years 11 months ago
A study on polynomial regression and Gaussian process global surrogate model in hierarchical surrogate-assisted evolutionary alg
This paper presents a study on Hierarchical Surrogate-Assisted Evolutionary Algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimiza...
Zongzhao Zhou, Yew-Soon Ong, My Hanh Nguyen, Dudy ...
EOR
2007
100views more  EOR 2007»
13 years 5 months ago
Parallel radial basis function methods for the global optimization of expensive functions
We introduce a master–worker framework for parallel global optimization of computationally expensive functions using response surface models. In particular, we parallelize two r...
Rommel G. Regis, Christine A. Shoemaker
ICDE
2001
IEEE
141views Database» more  ICDE 2001»
14 years 6 months ago
Processing Queries with Expensive Functions and Large Objects in Distributed Mediator Systems
LeSelect is a mediator system which allows scientists to publish their resources (data and programs) so they can be transparently accessed. The scientists can typically issue quer...
Fabio Porto, Françoise Fabret, Luc Bouganim...
GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
13 years 11 months ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya
GECCO
2009
Springer
14 years 1 days ago
Optimal robust expensive optimization is tractable
Following a number of recent papers investigating the possibility of optimal comparison-based optimization algorithms for a given distribution of probability on fitness functions...
Philippe Rolet, Michèle Sebag, Olivier Teyt...