Considering a positive portfolio diffusion X with negative drift, we investigate optimal stopping problems of the form inf θ E f  Xθ sup s∈[0,τ ] Xs   , where f is a non-increasing function, τ is the next random time where the portfolio X crosses zero and θ is any stopping time smaller than τ . Hereby, our motivation is the obtention of an optimal selling strategy minimizing the relativ...

This paper puts forward a comprehensive study of the design of global stopping criteria for multi-objective optimization. In this study we propose a global stopping criterion, which is terms as MGBM after the authors surnames. MGBM combines a novel progress indicator, called mutual domination rate (MDR) indicator, with a simplified Kalman filter, which is used for evidence-gathering purposes. T...

Restricted Boltzmann Machines (RBMs) are general unsupervised learning devices to ascertain generative models of data distributions. RBMs are often trained using the Contrastive Divergence learning algorithm (CD), an approximation to the gradient of the data log-likelihood. A simple reconstruction error is often used as a stopping criterion for CD, although several authors [1], [2] have raised ...

We combine linear algebra techniques with finite element techniques to obtain a reliable stopping cri-terion for Krylov method based algorithms. The Conjugate Gradient method has for a long time beensuccessfully used in the solution of the symmetric and positive definite systems obtained from thefinite-element approximation of self-adjoint elliptic partial differential equations...

Due to the growing complexity of todays technical systems optimization is becoming an important issue within the design phase. The applicability of optimization algorithms in automatic design processes is strongly dependent on the stopping criterion. It is important that the optimum is reliably found but furthermore no time or computational resources should be wasted. Therefore a run time analy...

In this article, a convergence criterion for the Monte Carlo estimates, which can be used as a stopping rule for the Monte Carlo experiments, will be proposed. The proposed criterion seeks a convergence band of a given width and length such that the probability of the Monte Carlo sample means to fall outside of this band is practically null. Although it has some sort of self defined confidence,...