Cross validation can be used to detect when overfitting starts during supervised training of a neural network; training is then stopped before convergence to avoid the overfitting ('early stopping'). The exact criterion used for cross validation based early stopping, however, is chosen in an ad-hoc fashion by most researchers or training is stopped interactively. To aid a more well-founded sele...

Inductive definitions and justifications are wellstudied concepts. Solvers that support inductive definitions have been developed, but several of their computationally nice properties have never been exploited to improve these solvers. In this paper, we present a new notion called relevance. We determine a class of literals that are relevant for a given definition and partial interpretation, an...

This paper presents a criterion for stopping non-linear iterative algorithms, specifically the Richardson-Lucy algorithm that is widely used to restore images from the Hubble Space Telescope. The criterion is based on generalized cross-validation and is also computed iteratively. We will present examples displaying the power of the stopping rule, and will discuss the abilities and shortcomings ...

Image segmentation is a critical step in computer vision tasks constituting an essential issue for pattern recognition and visual interpretation. In this paper, we propose a new stopping criterion for the mean shift iterative algorithm by using images defined in Zn ring, with the goal of reaching a better segmentation. We carried out also a study on the weak and strong of equivalence classes be...

Genetic Algorithm (GA) has now become one of the leading mechanisms in providing solution to complex optimization problems. Although widely used, there are very few theoretical guidelines for determining when to stop the algorithm. This article establishes theoretically that the variance of the best fitness values obtained in the iterations can be considered as a measure to decide the terminati...

This paper proposes a decision-tree backing-off technique for an HMM-based speech synthesis system. In the system, a decision-tree based context clustering technique is used for constructing parameter tying structures. In the context clustering, the MDL criterion has been used as a stopping criterion. In this paper, however, huge decision-trees are constructed without any stopping criterion. In...

We consider the problem of optimally stopping a general one-dimensional Itô diffusion X. In particular, we solve the problem that aims at maximising the performance criterion Ex [exp(− ∫ τ 0 r(Xs) ds)f (Xτ )] over all stopping times τ , where the reward function f can take only a finite number of values and has a ‘staircase’ form. This problem is partly motivated by applications to financial as...

Stopping accuracy is one of the most important indexes of efficiency of automatic train operation (ATO) systems. Traditional stopping control algorithms in ATO systems have some drawbacks, as many factors have not been taken into account. In the large amount of fieldcollected data about stopping accuracy there are many factors (e.g. system delays, stopping time, net pressure) which affecting st...

In Surrogate-based optimization, each optimization cycle consists of fitting a surrogate to a number of simulations at a set of design points, and performing optimization based on the surrogate to obtain one or more new design points. Algorithms like Efficient Global Optimization (EGO) [1] use uncertainty estimates available with the Kriging surrogate to guide the selection of new point(s). The...