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» A Data Locality Optimizing Algorithm
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110
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EMO
2001
Springer
107views Optimization» more  EMO 2001»
15 years 6 months ago
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
One common characterization of how simple hill-climbing optimization methods can fail is that they become trapped in local optima - a state where no small modi cation of the curren...
Joshua D. Knowles, Richard A. Watson, David Corne
212
Voted
ICDE
2008
IEEE
131views Database» more  ICDE 2008»
16 years 3 months ago
Parallel Evaluation of Composite Aggregate Queries
Aggregate measures summarizing subsets of data are valuable in exploratory analysis and decision support, especially when dependent aggregations can be easily specified and compute...
Lei Chen 0003, Christopher Olston, Raghu Ramakrish...
AAAI
1998
15 years 3 months ago
Optimal 2D Model Matching Using a Messy Genetic Algorithm
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
J. Ross Beveridge
113
Voted
ICASSP
2009
IEEE
15 years 9 months ago
Distributed subgradient projection algorithm for convex optimization
—We consider constrained minimization of a sum of convex functions over a convex and compact set, when each component function is known only to a specific agent in a timevarying...
Sundhar Srinivasan Ram, Angelia Nedic, Venugopal V...
CEC
2005
IEEE
15 years 7 months ago
Genetic algorithms with self-organized criticality for dynamic optimization problems
This paper proposes a genetic algorithm (GA) with random immigrants for dynamic optimization problems where the worst individual and its neighbours are replaced every generation. I...
Renato Tinós, Shengxiang Yang