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GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
13 years 10 months ago
Stochastic local search in continuous domains: questions to be answered when designing a novel algorithm
Several population-based methods (with origins in the world of evolutionary strategies and estimation-of-distribution algorithms) for black-box optimization in continuous domains ...
Petr Posik
GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
14 years 1 months ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague
JUCS
2008
139views more  JUCS 2008»
13 years 8 months ago
Parallel Strategies for Stochastic Evolution
: This paper discusses the parallelization of Stochastic Evolution (StocE) metaheuristic, for a distributed parallel environment. VLSI cell placement is used as an optimization pro...
Sadiq M. Sait, Khawar S. Khan, Mustafa Imran Ali
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
14 years 3 days ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
CEC
2005
IEEE
14 years 2 months ago
Effects of experience bias when seeding with prior results
Abstract- Seeding the population of an evolutionary algorithm with solutions from previous runs has proved to be useful when learning control strategies for agents operating in a c...
Mitchell A. Potter, R. Paul Wiegand, H. Joseph Blu...