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» A Graphical Model for Evolutionary Optimization
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GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 1 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
GECCO
2008
Springer
177views Optimization» more  GECCO 2008»
14 years 10 months ago
Reduced computation for evolutionary optimization in noisy environment
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
Maumita Bhattacharya
CVPR
2003
IEEE
15 years 11 months ago
Video Segmentation Based on Graphical Models
This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field...
Kia-Fock Loe, Tele Tan, Yang Wang 0002
EMO
2006
Springer
219views Optimization» more  EMO 2006»
15 years 1 months ago
ParadisEO-MOEO: A Framework for Evolutionary Multi-objective Optimization
Abstract. This paper presents ParadisEO-MOEO, a white-box objectoriented generic framework dedicated to the flexible design of evolutionary multi-objective algorithms. This paradig...
Arnaud Liefooghe, Matthieu Basseur, Laetitia Jourd...
EVOW
2009
Springer
15 years 4 months ago
Evolutionary Optimization Guided by Entropy-Based Discretization
The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Guleng Sheri, David W. Corne