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EC
2008
164views ECommerce» more  EC 2008»
13 years 8 months ago
Tracking Moving Optima Using Kalman-Based Predictions
The dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a timechanging fitness l...
Claudio Rossi, Mohamed Abderrahim, Julio Cé...
ICASSP
2010
IEEE
13 years 8 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
EPS
1998
Springer
14 years 14 days ago
Variable-Dimensional Optimization with Evolutionary Algorithms Using Fixed-Length Representations
This paper discusses a simple representation of variable-dimensional optimization problems for evolutionary algorithms. Although it was successfully applied to the optimization of ...
Joachim Sprave, Susanne Rolf
EC
2012
289views ECommerce» more  EC 2012»
12 years 3 months ago
Multimodal Optimization Using a Bi-Objective Evolutionary Algorithm
In a multimodal optimization task, the main purpose is to find multiple optimal solutions (global and local), so that the user can have a better knowledge about different optima...
Kalyanmoy Deb, Amit Saha
GECCO
2007
Springer
119views Optimization» more  GECCO 2007»
14 years 2 months ago
Optimising the flow of experiments to a robot scientist with multi-objective evolutionary algorithms
A Robot Scientist is a physically implemented system that applies artificial intelligence to autonomously discover new knowledge through cycles of scientific experimentation. Ad...
Emma Byrne