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GECCO
2009
Springer
194views Optimization» more  GECCO 2009»
15 years 6 months ago
Combining evolution strategy and gradient descent method for discriminative learning of bayesian classifiers
The optimization method is one of key issues in discriminative learning of pattern classifiers. This paper proposes a hybrid approach of the Covariance Matrix Adaptation Evolution...
Xuefeng Chen, Xiabi Liu, Yunde Jia
GECCO
2010
Springer
222views Optimization» more  GECCO 2010»
14 years 10 months ago
Black-box optimization benchmarking of NEWUOA compared to BIPOP-CMA-ES: on the BBOB noiseless testbed
In this paper, the performances of the NEW Unconstrained Optimization Algorithm (NEWUOA) on some noiseless functions are compared to those of the BI-POPulation Covariance Matrix A...
Nikolaus Hansen, Raymond Ros
AAMAS
2002
Springer
14 years 11 months ago
Adapting Populations of Agents
We control a population of interacting software agents. The agents have a strategy, and receive a payoff for executing that strategy. Unsuccessful agents become extinct. We investi...
Philippe De Wilde, Maria Chli, Luís Correia...
CEC
2008
IEEE
15 years 21 days ago
A technique for the visualization of population-based algorithms
— A technique for the visualization of stochastic population–based algorithms in multidimensional problems with known global minimizers is proposed. The technique employs proje...
Konstantinos E. Parsopoulos, Voula C. Georgopoulos...
GECCO
2004
Springer
15 years 5 months ago
The Lens Design Using the CMA-ES Algorithm
This paper presents a lens system design algorithm using the covariance matrix adaptation evolution strategy (CMA-ES), which is one of the most powerful self-adaptation mechanisms....
Yuichi Nagata