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» Neural Networks: A Replacement for Gaussian Processes
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GECCO
2011
Springer
264views Optimization» more  GECCO 2011»
12 years 11 months ago
Critical factors in the performance of novelty search
Novelty search is a recently proposed method for evolutionary computation designed to avoid the problem of deception, in which the fitness function guides the search process away...
Steijn Kistemaker, Shimon Whiteson
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
14 years 1 months ago
A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation
Surrogate-Assisted Memetic Algorithm(SAMA) is a hybrid evolutionary algorithm, particularly a memetic algorithm that employs surrogate models in the optimization search. Since mos...
Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendh...
NECO
2002
145views more  NECO 2002»
13 years 7 months ago
Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Aki Vehtari, Jouko Lampinen
TIT
2002
164views more  TIT 2002»
13 years 7 months ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini
AUSAI
2005
Springer
14 years 1 months ago
Accelerating Real-Valued Genetic Algorithms Using Mutation-with-Momentum
: In a canonical genetic algorithm, the reproduction operators (crossover and mutation) are random in nature. The direction of the search carried out by the GA system is driven pur...
Luke Temby, Peter Vamplew, Adam Berry