In this paper, we present a novel two-stage metric learning algorithm. We first map each learning instance to a probability distribution by computing its similarities to a set of fixed anchor points. Then, we define the distance in the input data space as the Fisher information distance on the associated statistical manifold. This induces in the input data space a new family of distance metric ...

We study two-stage choice procedures in which the decision maker first preselects the alternatives whose values according to a criterion pass a menu-dependent threshold and then maximizes a second criterion to narrow the selection further. This framework overlaps with several existing models that have various interpretations and impose various additional restrictions on behavior. We show that t...

In seismic data processing, deconvolution plays a very important role because it permits to increase the temporal resolution of seismic sections and to equalize sources. The deconvolution problem when the wavelet is known is an ill-posed problem that can be tackled via regularization methods. However, the seismic source wavelet is unknown and therefore, it must be estimated from the data prior ...

This paper presents the application of Two-Stage Programming (2sp) for developing error-free paral-lel/distributed applications through automatic verii-cation of computed results with respect to a given speciication. The presentation focuses the case study of the parallel block-striped partitioning variant of Prim's algorithm for nding a minimum spanning tree of a dense graph. We show that the ...

Parallel block two-stage iterative methods for the solution of linear systems of algebraic equations are studied. Convergence is shown for monotone matrices and for H-matrices. Two diierent asynchronous versions of these methods are considered and their convergence investigated.

Nowadays, most of products are the results of different dependent process steps. Due to the cascade property in most of these processes, using the traditional control charts for monitoring these processes is not suitable. To solve this problem, Cause selecting Charts (CSCs) are developed to monitor multistage processes. These control charts have usually been developed when quality characteristi...

In this study, we propose a control chart for monitoring two-stage processes whose quality characteristic to be monitored in the second stage follows a binomial distribution. The proposed control chart is based on the deviance residual which essentially the generalized log-likelihood ratio statistic is obtained from the generalized linear model. To establish the relationship between the firstan...

In the prior literature onmeasuring the efficiency of two-stage processes, there are both radial and non-radial methods of efficiency measurement. In some cases, non-radial methods which allow all inputs, intermediate measures and outputs to change non-proportionally are more appropriate than radial methods, but they do not ensure stage efficiency or allow for the efficiency decomposition of tw...

This paper motivates and introduces a two-stage method of estimating diffusion processes based on discretely sampled observations. In the first stage we make use of the feasible central limit theory for realized volatility, as developed in [Jacod, J., 1994. Limit of random measures associated with the increments of a Brownian semiartingal. Working paper, Laboratoire de Probabilities, Universite...