A Study of Deep Learning Robustness Against Computation Failures

For many types of integrated circuits, accepting larger failure rates in computations can be used to improve energy efficiency. We study the performance of faulty implementations of certain deep neural networks based on pessimistic and optimistic models of the effect of hardware faults. After identifying the impact of hyperparameters such as the number of layers on robustness, we study the ability of the network to compensate for computational failures through an increase of the network size. We show that some networks can achieve equivalent performance under faulty implementations, and quantify the required increase in computational complexity

A simple and flexible alternative to the Stability and Growth Pact deficit ceilings. Is it at hand?

We use a simple theoretical model of a monetary union where myopic discretionary fiscal policies generate excessive debt accumulation in steady state and inefficiently delayed debt adjustment following a shock. We advocate the adoption of a flexible debt targeting approach. By setting a long-term debt target and by raising the political cost associated to deviations from the optimal pace of debt reversal following a shock¸ institutional design induces the fiscal policymaker to implement unbiased discretionary responses to shocks. Since the power to discipline fiscal policymakers rests in the hands of national voters, this outcome can be achieved by increasing the transparency of the decision-making process, where national voters understand the long-term consequences of fiscal policies. In practice, we call for clearer and more focused supervision tasks for the European Commission and for a more active role of national Parliaments whenever a disagreement arises between the Commission and a national government.

On the interplay between consistency, completeness, and correctness in requirements evolution

The initial expression of requirements for a computer-based system is often informal and possibly vague. Requirements engineers need to examine this often incomplete and inconsistent brief expression of needs. Based on the available knowledge and expertise, assumptions are made and conclusions are deduced to transform this 'rough sketch' into more complete, consistent, and hence correct requirements. This paper addresses the question of how to characterize these properties in an evolutionary framework, and what relationships link these properties to a customer's view of correctness. Moreover, we describe in rigorous terms the different kinds of validation checks that must be performed on different parts of a requirements specification in order to ensure that errors (i.e. cases of inconsistency and incompleteness) are detected and marked as such, leading to better quality requirements. © 2003 Elsevier B.V. All rights reserved