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TEC
2008
165views more  TEC 2008»
13 years 10 months ago
Population-Based Incremental Learning With Associative Memory for Dynamic Environments
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its importance in real-world applications. Several app...
Shengxiang Yang, Xin Yao
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
14 years 4 months ago
Population-based incremental learning with memory scheme for changing environments
In recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several a...
Shengxiang Yang
EVOW
2006
Springer
14 years 2 months ago
Associative Memory Scheme for Genetic Algorithms in Dynamic Environments
In recent years dynamic optimization problems have attracted a growing interest from the community of genetic algorithms with several approaches developed to address these problems...
Shengxiang Yang
ML
2008
ACM
13 years 10 months ago
Incremental exemplar learning schemes for classification on embedded devices
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
Ankur Jain, Daniel Nikovski
CEC
2009
IEEE
14 years 5 months ago
Hyper-learning for population-based incremental learning in dynamic environments
— The population-based incremental learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning. Recently, the PBIL algorithm has been applied...
Shengxiang Yang, Hendrik Richter