In this paper, we compare the BFGS and the conjugate gradient (CG) methods for solving unconstrained problems with a trust-region algorithm. The main result ...

This paper targets a stochastic energy management problem. We first decouple the stochasticity of the global scenarios to local scenarios. Then, we use spat...

In Positron Emission Tomography (PET), deep crystals (>20 mm) must be used to enhance detection efficiency and increase overall scanner sensitivity. Howeve...

Positron emission tomography (PET) image reconstruction in the presence of periodic motion, such as heartbeat and breathing, has been actively investigated ...

Adaptative cubic regularization (ARC) methods for unconstrained optimization compute steps from linear systems with a shifted Hessian in the spirit of the mo...

In this work, we examine how to combine the score function method with the standard crude Monte Carlo and experimental design approaches, in order to evalua...

It is well-known (see Pang and Chan [7]) that Newton's method, applied to strongly monotone variational inequalities, is locally and quadratically convergent...

Applied to strongly monotone variational inequality problems, Newton's algorithm achieves local quadratic convergence. However, global convergence cannot be...