For many real-life engineering optimization problems, the cost of one objective function evaluation can take several minutes or hours. In this context, a popular approach to reduce...
In parallel and distributed processing, tasks are ordinarily clustered and assigned to different processors or machines before they are scheduled. The assignment of tasks to proc...
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Tomographic reconstruction from positron emission tomography (PET) data is an ill-posed problem that requires regularization. An attractive approach is to impose an 1-regularizatio...
J. Verhaeghe, Dimitri Van De Ville, I. Khalidov, Y...
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...