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GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 3 months ago
Greedy, genetic, and greedy genetic algorithms for the quadratic knapsack problem
Augmenting an evolutionary algorithm with knowledge of its target problem can yield a more effective algorithm, as this presentation illustrates. The Quadratic Knapsack Problem e...
Bryant A. Julstrom
EC
2000
171views ECommerce» more  EC 2000»
14 years 9 months ago
Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions
Building blocks are a ubiquitous feature at all levels of human understanding, from perception through science and innovation. Genetic algorithms are designed to exploit this prev...
John H. Holland
CORR
2010
Springer
100views Education» more  CORR 2010»
14 years 9 months ago
The Projected GSURE for Automatic Parameter Tuning in Iterative Shrinkage Methods
Linear inverse problems are very common in signal and image processing. Many algorithms that aim at solving such problems include unknown parameters that need tuning. In this work...
Raja Giryes, Michael Elad, Yonina C. Eldar
71
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AIIA
2007
Springer
15 years 3 months ago
A Comparison of Genetic Algorithms for Optimizing Linguistically Informed IR in Question Answering
In this paper we compare four selection strategies in evolutionary optimization of information retrieval (IR) in a question answering setting. The IR index has been augmented by li...
Jörg Tiedemann
CGO
2004
IEEE
15 years 1 months ago
A Dynamically Tuned Sorting Library
Empirical search is a strategy used during the installation of library generators such as ATLAS, FFTW, and SPIRAL to identify the algorithm or the version of an algorithm that del...
Xiaoming Li, María Jesús Garzar&aacu...