In: Cancers, 2021, vol. 13, no. 19, p. 18
Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g., machine learning and deep learning, as well as the recently developed research field of radiomics have noticeable potential to transform medical diagnostics. AI-based techniques applied to medical imaging allow to detect biological abnormalities, to...
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In: Algorithms, 2021, vol. 14, no. 9, p. 25
Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be...
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In: Empirical Software Engineering, 2020, vol. 25, no. 6, p. 5193–5254
Context: A Machine Learning based System (MLS) is a software system including one or more components that learn how to perform a task from a given data set. The increasing adoption of MLSs in safety critical domains such as autonomous driving, healthcare, and finance has fostered much attention towards the quality assurance of such systems. Despite the advances in software testing, MLSs bring...
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Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO011.
Personal computing systems like e.g., laptop, smartphone, and smartwatches are nowadays ubiquitous in people's everyday life. People use such systems not only for communicating or searching for information, but also as digital companions, able to track and support their daily activities such as sleep, food intake, physical exercise and even work. Sensors embedded in personal computing systems...
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Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO009.
Advances on psycho-linguistics have evidenced that the ways in which people use words could act as a reliable source to assess a wide array of behaviours. Language use acts as an indicator of the individuals’ current mental state, personality and even personal values. In this thesis, we focus on language analysis to study two closely related processes which encompass integral components of...
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Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO017.
Complex multi-tier systems are composed of many distributed machines, feature multi-layer architecture and offer different types of services. Shared complex multi-tier systems, such as cloud systems, reduce costs and improves resource utilization efficiency, with a considerable amount of complexity and dynamics that challenge the reliability of the system. The new challenges of complex...
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Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO020.
Stochastic Optimization Problems take uncertainty into account. For this reason they are in general more realistic than deterministic ones, meanwhile, more difficult to solve. The challenge is both on modelling and computation aspects: exact methods usually work only for small instances, besides, there are several problems with no closed-form expression or hard- to-compute objective functions....
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Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020ECO007.
Empirical indicators of sentiment are commonly employed in the economic literature while a precise understanding of what is sentiment is still missing. Exploring the links among the most popular proxies of sentiment, fear and uncertainty this paper aims to fill this gap. We show how fear and sentiment are specular in their predictive power in relation to the aggregate market and to...
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Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020ECO002.
My dissertation consists of three chapters, each of which focuses on a different area of research in asset pricing. The first chapter deals with the informational role of brokerage firms during fire sales in the equity market. The second chapter exploits the ETF program by the bank of Japan as a quasi-natural experiment to measure the slope of the equity demand curve. The last chapter presents...
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In: Entropy, 2019, vol. 21, no. 8, p. 758
Variational inference with a factorized Gaussian posterior estimate is a widely-used approach for learning parameters and hidden variables. Empirically, a regularizing effect can be observed that is poorly understood. In this work, we show how mean field inference improves generalization by limiting mutual information between learned parameters and the data through noise. We quantify a...
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