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» A Graphical Model for Evolutionary Optimization
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135
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GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 6 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»
15 years 3 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
16 years 4 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
143
Voted
EMO
2006
Springer
219views Optimization» more  EMO 2006»
15 years 6 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...
126
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EVOW
2009
Springer
15 years 9 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