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ESANN
2004
13 years 10 months ago
Evolutionary Optimization of Neural Networks for Face Detection
For face recognition from video streams speed and accuracy are vital aspects. The first decision whether a preprocessed image region represents a human face or not is often made by...
Stefan Wiegand, Christian Igel, Uwe Handmann
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 3 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart
SEAL
1998
Springer
14 years 1 months ago
Robust Evolution Strategies
This paper empirically investigates the use and behaviour of Evolution Strategies (ES) algorithms on problems such as function optimisation and the use of evolutionary artificial ...
Kazuhiro Ohkura, Yoshiyuki Matsumura, Kanji Ueda
GECCO
2008
Springer
168views Optimization» more  GECCO 2008»
13 years 10 months ago
A multi-start quantum-inspired evolutionary algorithm for solving combinatorial optimization problems
Quantum-inspired evolutionary algorithms (QIEAs), as a subset of evolutionary computation, are based on the principles of quantum computing such as quantum bits and quantum superp...
Parvaz Mahdabi, Saeed Jalili, Mahdi Abadi
GECCO
2006
Springer
153views Optimization» more  GECCO 2006»
14 years 29 days ago
On the local performance of simulated annealing and the (1+1) evolutionary algorithm
Simulated annealing and the (1+1) EA, a simple evolutionary algorithm, are both general randomized search heuristics that optimize any objective function with probability
Thomas Jansen, Ingo Wegener