Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO005.
Many relevant discrete optimization problems are believed to be hard to solve efficiently (i.e. they cannot be solved in polynomial time unless P=NP). An approximation algorithm is one of the ways to tackle these hard optimization problems. These algorithms have polynomial running time and compute a feasible solution whose value is within a proven factor (approximation factor) of the optimal...
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Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO004.
Digital library (DL) systems in the last decade have provided an unprecedented access to library content that were confined to their physical spaces. The last twenty years of the DL system renovation have witnessed several generations of online catalogs from the Online Public Access Catalogue (OPAC) late 1980s, to the next generation catalog systems (NGC). DL systems are extensively used to...
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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 ; 2020INFO023.
As energy efficiency becomes a crucial concern in almost every kind of digital application, Approximate Computing gains popularity as a potential answer to this ever-growing energy quest. Approximate Computing is a design paradigm particularly suited for error- resilient applications, where small losses in accuracy do not represent a significant reduction in the quality of the result. In these...
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Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO003.
Blockchains are a new type of state machine replication that have raised interesting challenges. A replicated state machine (RSM) is a well-established approach to building fault-tolerant systems. Because each replica needs to execute the same set of instructions to transition through the same state changes, adding more replicas does not translate directly to an increase in performance. On top...
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Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO002.
Recent trends in industry show increasing adoption of Development and Operations (DevOps) practices. Reasons for increasing DevOps adoption are the focus on the creation of cross-functional teams, and the ability to release high-quality software at a fast pace. Alongside the adoption of DevOps, performance testing continues to evolve to meet the growing demands of the modern enterprise and its...
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Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO021.
The field of scientific computing is associated with the modeling of complex physical phenomena. The resulting numerical models are often described by differential equations, which, in many cases, can be related to non-convex minimization problems. Thus, after discretization, the solution of large-scale non-convex optimization problem is required. Various iterative solution strategies can be...
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Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO001.
Digitalization is all around us, even more so in pandemic times where substantial part of our lives has been moved online. One of the key enablers of digitalization are the Application Programming Interfaces (APIs) which enable the communication and exchange of data between different systems. They abstract from the implementation details of the underlying systems and allow for the monetization...
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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 ; 2020INFO019.
Deep neural networks learn representations of data to facilitate problem-solving in their respective domains. However, they struggle to acquire a structured representation based on more symbolic entities, which are commonly understood as core abstractions central to human capacity for generalization. This dissertation studies this issue for visual reasoning tasks. Inspired by how humans solve...
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