In this paper, we are concerned with the stability of the error bounds for semi-infinite convex constraint systems. Roughly speaking, the error bound of a system of inequalities is said to be stable if all its “small” perturbations admit a (local or global) error bound. We first establish subdifferential characterizations of the stability of error bounds for semi-infinite systems of convex ineq...

This paper considers the simple step-stress model from the Marshall-Olkin generalized exponential distribution when there is time constraint on the duration of the experiment. The maximum likelihood equations for estimating the parameters assuming a cumulative exposure model with lifetimes as the distributed Marshall Olkin generalized exponential are derived. The likelihood equations do not lea...

According to the OT error-driven ranking model of language acquisition, the learner performs a sequence of slight re-rankings triggered by mistakes on the incoming stream of data, until it converges to a ranking that makes no more mistakes. This learning model is very popular in the OT acquisition literature, in particular because it predicts a sequence of rankings that models gradualness in ch...

With the arrival of high throughput genotyping techniques, the detection of likely genotyping errors is becoming an increasingly important problem. In this paper we are interested in errors that violate Mendelian laws. The problem of deciding if Mendelian error exists in a pedigree is NP-complete [1]. Existing tools dedicated to this problem may offer different level of services: detect simple ...

In this paper, a general error analysis is provided for finite-element discretizations of partial differential equations in a saddle-point form with divergence constraint. In particular, this extends upon the work of [J. H. Adler and P. S. Vassilevski, Springer Proc. Math. Statist. 45, Springer, New York, 2013, pp. 1–19], giving a general error estimate for finite-element problems augmented wit...

In this work we introduce a novel approach, based on sampling, for finding policies that are likely to be solutions to stochastic constraint satisfaction problems and constraint optimisation problems. Our approach reduces the size of the original problem being analysed and it guarantees that, with a given confidence probability, the policies produced by solving this reduced problem satisfy the ...

We present a new family of algorithms that solve the bias problem in the equation-error based adaptive in nite impulse response (IIR) ltering. A novel constraint, called the constant-norm constraint, uni es the quadratic constraint and the monic one. By imposing the monic constraint on the mean square error (MSE) optimization, the merits of both constraints are inherited and the shortcomings ar...

Unlike existing global shape-from-shading (SFS) algorithms which involve the brightness constraint in their formulation, we propose a new SFS algorithm which replaces the brightness constraint with an intensity gradient constraint. This is a global approach which obtains the solution by the minimization of an error function over the entire image. Through the linearization of the gradient of the...

Shape-based registration is a process for estimating the transformation between two shape representations of an object. It is used in many image-guided surgical systems to establish a transformation between preand intra-operative coordinate systems. This paper describes several tools which are useful for improving the accuracy resulting from shape-based registration: constraint analysis, constr...

This paper studies constrained relative attitude determination of a formation of two vehicles. A deterministic solution for the relative attitude between the two vehicles with line-of-sight observations between them and a common object observed by both vehicles is presented. The constraint may be either a planar constraint or a triangle constraint of the observed vectors. The difference between...