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: Future internet, 2021, vol. 13, no. 9, p. 12
As part of studies that employ health electronic records databases, this paper advocates the employment of graph theory for investigating drug-switching behaviors. Unlike the shared approach in this field (comparing groups that have switched with control groups), network theory can provide information about actual switching behavior patterns. After a brief and simple introduction to...
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In: Journal of computational science, 2021, vol. 53, p. 13
The ℓ1-regularized Gaussian maximum likelihood method is a common approach for sparse precision matrix estimation, but one that poses a computational challenge for high-dimensional datasets. We present a novel ℓ1- regularized maximum likelihood method for performant large-scale sparse precision matrix estimation utilizing the block structures in the underlying computations. We identify the...
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In: Algorithms, 2020, vol. 13, no. 12, p. 17
Incomplete data are a common feature in many domains, from clinical trials to industrial applications. Bayesian networks (BNs) are often used in these domains because of their graphical and causal interpretations. BN parameter learning from incomplete data is usually implemented with the Expectation-Maximisation algorithm (EM), which computes the relevant sufficient statistics (“soft EM”) ...
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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 ; 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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Mémoire de master : Haute école de gestion de Genève, 2020 ; MASID 104.
Maritime transportation plays an important role in the world’s economy, representing 70-80% of all trade. Due its vital status, since 2004 the Automatic Identification System (AIS), provides information on vessel movement by means of electronic data. A ship is required to broadcast a message describing its position, destination, etc. every 2 to 10 seconds while moving. The signal’s...
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In: ACM transactions on graphics, 2020, vol. 39, no. 4, p. 16 p
Digital drawing tools are now standard in art and design workflows. These tools offer comfort, portability, and precision as well as native integration with digital-art workflows, software, and tools. At the same time, artists continue to work with long-standing, traditional drawing tools. One feature of traditional tools, well-appreciated by many artists and lacking in digital tools, is the...
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In: Entropy, 2019, vol. 21, no. 2, p. 104
In view of the importance of quantum non-locality in cryptography, quantum computation, and communication complexity, it is crucial to decide whether a given correlation exhibits non-locality or not. As proved by Pitowski, this problem is NP- complete, and is thus computationally intractable unless NP is equal to P. In this paper, we first prove that the Euclidean distance of given...
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In: Entropy, 2017, vol. 19, no. 7, p. 326-334
Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a novel computing paradigm beyond quantum computing, replacing this assumption by mere logical consistency: We study non-causal circuits, where a fixed time...
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