首页|Reports Summarize Computational Intelligence Study Results fromNortheastern Uni versity (Surrogate-assisted Evolutionary Multiobjective Optimization of Medium- scale Problems By Random Grouping and Sparse Gaussian Modeling)
Reports Summarize Computational Intelligence Study Results fromNortheastern Uni versity (Surrogate-assisted Evolutionary Multiobjective Optimization of Medium- scale Problems By Random Grouping and Sparse Gaussian Modeling)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning - Computational Intelligence.According to news reporting origi nating from Shenyang, People’s Republic of China, by NewsRx correspondents,rese arch stated, “Gaussian processes (GPs) are widely employed in surrogate-assisted evolutionaryalgorithms (SAEAs) because they can estimate the level of uncertai nty in their predictions. However, thecomputational complexity of GPs grows cub ically with the number of training samples, the time requiredfor constructing a GP becomes excessively long.”
ShenyangPeople’s Republic of ChinaAs iaComputational IntelligenceMachine LearningEvolutionary AlgorithmMathem aticsNortheastern University
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