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GECCO
2009
Springer
107views Optimization» more  GECCO 2009»
13 years 10 months ago
A stigmergy-based algorithm for black-box optimization: noisy function testbed
In this paper, we present a stigmergy-based algorithm for solving optimization problems with continuous variables, labeled Differential Ant-Stigmergy Algorithm (DASA). The perfor...
Peter Korosec, Jurij Silc
GECCO
2009
Springer
130views Optimization» more  GECCO 2009»
13 years 10 months ago
A stigmergy-based algorithm for black-box optimization: noiseless function testbed
In this paper, we present a stigmergy-based algorithm for solving optimization problems with continuous variables, labeled Differential Ant-Stigmergy Algorithm (DASA). The perfor...
Peter Korosec, Jurij Silc
ICML
1998
IEEE
14 years 6 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
GECCO
2009
Springer
142views Optimization» more  GECCO 2009»
13 years 10 months ago
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 noisy testbed
We benchmark an independent-restart-(1+1)-CMA-ES on the BBOB-2009 noisy testbed. The (1+1)-CMA-ES is an adaptive stochastic algorithm for the optimization of objective functions d...
Anne Auger, Nikolaus Hansen
GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
13 years 10 months ago
Benchmarking the BFGS algorithm on the BBOB-2009 noisy testbed
The BFGS quasi-Newton method is benchmarked on the noisy BBOB-2009 testbed. A multistart strategy is applied with a maximum number of function evaluations of about 104 times the s...
Raymond Ros