One of the most significant problems in the development of quantitative models to assess the performance of decision-making units (DMUs) is the availability of information coded into variables and indicators that are proxies for the relevant dimensions of the models: resources or inputs, products...
01a Articolo in rivista
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In the 2000s, Italy liberalized its electricity and natural gas markets, and in 2016, it separated retail activities from other activities within these markets. Such differentiation is unique within Europe. Italy is an ideal case for investigating which operational factors may increase profit...
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This paper presents a Federated Learning (FL) algorithm that allows the decentralization of all FL solutions that employ a model-averaging procedure. The proposed algorithm proves to be capable of attaining faster convergence rates and no performance loss against the starting centralized FL...
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Today’s Internet is experiencing a massive number of users with a continuously increasing need for data, which is the leading cause of introduced limitations among security and privacy issues. To overcome these limitations, a shift from host-centric to data-centric is proposed, and in this context...
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Federated Learning (FL) represents the de facto approach for distributed training of machine learning models. Nevertheless, researchers have identified several security and privacy FL issues. Among these, the lack of anonymity exposes FL to linkability attacks, representing a risk for model...
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Multiple-choice questions (MCQs) are widely used in educational assessments and professional certification exams. Managing large repositories of MCQs, however, poses several challenges due to the high volume of questions andthe need to maintain their quality and relevance over time. One of these...
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In this article, we introduce and discuss the pervasive issue of bias in the large language models that are currently at the core of mainstream approaches to Natural Language Processing (NLP). We first introduce data selection bias, that is, the bias caused by the choice of texts that make up a...
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This paper studies the monotonicity of equilibrium costs and equilibrium loads in nonatomic congestion games, in response to variations of the demands. The main goal is to identify conditions under which a paradoxical non-monotone behavior can be excluded. In contrast with routing games with a...
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In this paper, we consider the optimization problem of minimizing a continuously differentiable function subject to both convex constraints and sparsity constraints. By exploiting a mixed-integer reformulation from the literature, we define a necessary optimality condition based on a tailored...
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Acoustic underwater channels are very challenging, because of limited bandwidth, long propagation delays, extended multipath, severe attenuation, rapid time variation and large Doppler shifts. A plethora of underwater communication techniques have been developed for dealing with such a complexity,...