In this paper, a ridgelet kernel regression model is proposed for approximation of high dimensional functions. It is based on ridgelet theory, kernel and regularization technology ...
— A technique for the visualization of stochastic population–based algorithms in multidimensional problems with known global minimizers is proposed. The technique employs proje...
Konstantinos E. Parsopoulos, Voula C. Georgopoulos...
Power consumption is becoming a primary concern as a result of tremendous increasing in computer power usage. Innumerable methods and techniques have been exploited to address thi...
Rigorous runtime analyses of evolutionary algorithms (EAs) mainly investigate algorithms that use elitist selection methods. Two algorithms commonly studied are Randomized Local S...
Edda Happ, Daniel Johannsen, Christian Klein, Fran...
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...