Abstract not found

This paper considers the classical error correcting problem which is frequently discussed in coding theory. We wish to recover an input vector f ∈ Rn from corrupted measurements y = Af + e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible

. This framework can handle errors due to occlusion and corruption uniformly, by exploiting the fact that these errors are often sparse w.r.t. to the standard (pixel) basis. The theory of sparse representation helps predict how much occlusion the recognition algorithm can handle and how to choose the training

Experiment with Northern and Southern Italians

This paper uses a randomized field experiment to examine several approaches to reducing corruption. I measure missing expenditures in over 600 village road projects in Indonesia by having engineers independently estimate the prices and quantities of all inputs used in each road, and then comparing

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. The result is a host-based intrusion detection system with three advantages: a high degree of automation, protection against a broad class of attacks based on corrupted code, and the elimination of false alarms. We report on our experience with a prototype implementation of this technique. 1. Introduction

Some years ago I interviewed the chief executive officer of a successful Thai manufacturing firm as part of a pilot survey project. While trying to figure out a good way to quantify the firm’s experience with government regulations and corruption in the foreign trade sector, the CEO exclaimed: “I

nowadays that corruption does have a negative impact on (foreign) private investment and growth, government revenue and infrastructure, and social equality, and while there seems to be evidence that low economic development, federal structure and short histories of experience with democracy and free trade

we don't know and that it does not depend upon our life experiences. It is this type of trust that binds us to others. Trusting people are more likely to volunteer their time, to give to charity, to be tolerant of others, and to support policies that both promote economic growth (open markets