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WSC
1997
13 years 10 months ago
Comparison of Monte Carlo and Deterministic Methods for Non-Adaptive Optimization
In this paper we compare the average performance of Monte Carlo methods for global optimization with non-adaptive deterministic alternatives. We analyze the behavior of the algori...
Hisham A. Al-Mharmah, James M. Calvin
EWC
2006
120views more  EWC 2006»
13 years 8 months ago
A comparison of two optimization methods for mesh quality improvement
We compare inexact Newton and block coordinate descent optimization methods for improving the quality of a mesh by repositioning the vertices, where the overall quality is measure...
Lori Freitag Diachin, Patrick M. Knupp, Todd S. Mu...
GECCO
2010
Springer
195views Optimization» more  GECCO 2010»
13 years 6 months ago
Black-box optimization benchmarking the IPOP-CMA-ES on the noiseless testbed: comparison to the BIPOP-CMA-ES
We benchmark the Covariance Matrix Adaptation-Evolution Strategy (CMA-ES) algorithm with an Increasing POPulation size (IPOP) restart policy on the BBOB noiseless testbed. The IPO...
Raymond Ros
GECCO
2007
Springer
147views Optimization» more  GECCO 2007»
14 years 21 days ago
A comparison of evaluation methods in coevolution
In this research, we compare four different evaluation methods in coevolution on the Majority Function problem. The size of the problem is selected such that an evaluation against...
Ting-Shuo Yo, Edwin D. de Jong
ICALP
2011
Springer
13 years 8 days ago
Content Search through Comparisons
We study the problem of navigating through a database of similar objects using comparisons. This problem is known to be strongly related to the small-world network design problem....
Amin Karbasi, Stratis Ioannidis, Laurent Massouli&...