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GECCO
2008
Springer
363views Optimization» more  GECCO 2008»
15 years 5 months ago
Towards high speed multiobjective evolutionary optimizers
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder
SG
2005
Springer
15 years 10 months ago
Multi-level Interaction in Parametric Design
Parametric design systems model a design as a constrained collection of schemata. Designers work in such systems at two levels: definition of schemata and constraints; and search w...
Robert Aish, Robert Woodbury
BMCBI
2011
14 years 11 months ago
Simulated evolution applied to study the genetic code optimality using a model of codon reassignments
Background: As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical ge...
Jose Santos, Ángel Monteagudo
IJCV
2000
133views more  IJCV 2000»
15 years 4 months ago
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...
Yoram Leedan, Peter Meer
INFOCOM
2012
IEEE
13 years 7 months ago
Approximately optimal adaptive learning in opportunistic spectrum access
—In this paper we develop an adaptive learning algorithm which is approximately optimal for an opportunistic spectrum access (OSA) problem with polynomial complexity. In this OSA...
Cem Tekin, Mingyan Liu