Today’s intensive demand for data such as live broadcast or news feeds requires efficient and robust dissemination systems. Traditionally, designs focus on extremes of the efficiency/robustness spectrum by either using structures, such as trees for efficiency or by using loosely-coupled epidemic protocols for

The efficiency of the robust estimation approach based on the information about the variances of the signal itself and its several derivatives is analyzed. Comprehensive comparison of robust and optimal estimators is performed. It is shown that the robust estimator suggested provides the reliable and precise signal estimation in the presence of noise. The obtained theoretical results are illust...

This paper describes a software package for computing nonparametric efficiency estimates, making inference, and testing hypotheses in frontier models. Commands are provided for bootstrapping as well as computation of some new, robust estimators of efficiency, etc. JEL classification: C14; C15; C44

We present a scheme for linear optical quantum computation that is highly robust to imperfect single photon sources and inefficient detectors. In particular we show that if the product of the detector efficiency with the source efficiency is greater than 2/3, then efficient linear optical quantum computation is possible. This high threshold is achieved within the cluster state paradigm for quan...

Robust optimization is typically based on repeated calls to a deterministic simulation program that aim at both propagating uncertainties and finding optimal design variables. Often in practice, the ”simulator” is a computationally intensive software which makes the computational cost one of the principal obstacles to optimization in the presence of uncertainties. This article proposes a new ef...

In spacecraft engineering a paradigm shift is emerging with the tendency from traditional, single, large, and multifunctional satellites towards cooperating, distributed small spacecraft systems. In particular modern miniaturization techniques allow realization of satellites with continuously smaller masses, and thus enable cost-efficient implementation and launch of distributed multi-satellite...

This paper deals with biobjective combinatorial optimization problems where both objectives are required to be well-balanced. Lorenz dominance is a refinement of the Pareto dominance that has been proposed in economics to measure the inequalities in income distributions. We consider in this work the problem of computing the Lorenz optimal solutions to combinatorial optimization problems where s...

We consider the minimax setup for the two-armed bandit problem as applied to data processing if there are two alternative processing methods available with different a priori unknown efficiencies. One should determine the most effective method and provide its predominant application. To this end we use the mirror descent algorithm (MDA). It is well-known that corresponding minimax risk has the ...

We propose a tractable approximation scheme for convex (not necessarily linear) multi-stage robust optimization problems. We approximate the adaptive decisions by finite linear combinations of prescribed basis functions and demonstrate how one can optimize over these decision rules at low computational cost through constraint randomization. We obtain a-priori probabilistic guarantees on the fea...

An approach making use of SURF feature and Adaboost for hand posture recognition is proposed. First the SURF key points are extracted to describe the blob or ridge-like structures from grey level images. These are potential points of interest that can be used to match with other images with similar structures. Then the statistic parameters of the tendency of gradient changes within small patche...