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GECCO
2009
Springer
107views Optimization» more  GECCO 2009»
13 years 9 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 9 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 5 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 9 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 9 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