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A teaching-learning-based optimization algorithm for solving set covering problems
(Springer Verlag, 2015)
The set covering problem solved by the binary teaching-learning-based optimization algorithm [Problema del Conjunto de Cobertura Resuelto Mediante el Algoritmo Binario de Optimización Basado en Enseñanza- Aprendizaje]
(Institute of Electrical and Electronics Engineers Inc., 2015)
A new implementation of Population Based Incremental Learning method for optimization studies in electromagnetics
(2006-11-21)
To enhance the global search ability of Population Based Incremental Learning (PBIL) methods, It Is proposed that multiple probability vectors are to be Included on available PBIL algorithms. As a result, the strategy for ...
Optimal transport for machine learning: theory and applications
(2021-03-25)
O que os operadores de produção de petróleo valorizam ao comprar produtos químicos?: uma análise sobre a percepção de valor na decisão de compra ou contratação de um provedor de especialidades químicas no mercado de óleo ...
Meta-heuristic multi- and many-objective optimization techniques for solution of machine learning problems
(Wiley-Blackwell, 2017-12-01)
Recently, multi- and many-objective meta-heuristic algorithms have received considerable attention due to their capability to solve optimization problems that require more than one fitness function. This paper presents a ...
Learning motion: Human vs. optimal Bayesian learner
(Pergamon-Elsevier Science Ltd, 2010-02)
We used the optimal perceptual learning paradigm (Eckstein, Abbey, Pham, & Shimozaki, 2004) to investigate the dynamics of human rapid learning processes in motion discrimination tasks and compare it to an optimal Bayesian ...
Seller-optimal learning and monopsony pricing
(2018-03-28)
This paper studies incentives for information gathering in a monoposonist pricing setting. Our motivation stems from public procurement contracts where the government is the single buyer, and the true cost of providing the ...
A new implementation of population based incremental learning method for optimizations in electromagnetics
(Institute of Electrical and Electronics Engineers (IEEE), 2007-04-01)
To enhance the global search ability of population based incremental learning (PBIL) methods, it is proposed that multiple probability vectors are to be included on available PBIL algorithms. The strategy for updating those ...