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Università della Svizzera italiana

Block-enhanced precision matrix estimation for large-scale datasets

Eftekhari, Aryan ; Pasadakis, Dimosthenis ; Bollhöfer, Matthias ; Scheidegger, Simon ; Schenk, Olaf

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...

Università della Svizzera italiana

Discrimination of non-local correlations

Montina, Alberto ; Wolf, Stefan

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...

Università della Svizzera italiana

Optimization of anchor nodes placement in wireless localization networks

Balac, Katarina ; Malek, Miroslaw (Dir.) ; Prevostini, Mauro (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2019 ; 2019INFO009.

This work focuses on optimizing node placement for time-of-flight-based wireless localization networks. Main motivation are critical safety applications. The first part of my thesis is an experimental study on in-tunnel vehicle localization. In- tunnel localization of vehicles is crucial for emergency management, especially for large trucks transporting dangerous goods such as inflammable...

Università della Svizzera italiana

Efficient combinatorial optimization algorithms for logistic problems

Papapanagiotou, Vasileios ; Gambardella, Luca Maria (Dir.) ; Montemanni, Roberto (Codir.) ; Schmidhuber, Jürgen (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2018 ; 2018INFO011.

The field of logistics and combinatorial optimization features a wealth of NP-hard problems that are of great practical importance. For this reason it is important that we have efficient algorithms to provide optimal or near-optimal solutions. In this work, we study, compare and develop Sampling-Based Metaheuristics and Exact Methods for logistic problems that are important for their...

Università della Svizzera italiana

Self-adaptivity of applications on network on chip multiprocessors : the case of fault-tolerant Kahn process networks

Derin, Onur ; Sami, Mariagiovanna (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2015 ; 2015INFO010.

Technology scaling accompanied with higher operating frequencies and the ability to integrate more functionality in the same chip has been the driving force behind delivering higher performance computing systems at lower costs. Embedded computing systems, which have been riding the same wave of success, have evolved into complex architectures encompassing a high number of cores interconnected...

Università della Svizzera italiana

Stochastic vehicle routing : from theory to practice

Weyland, Dennis ; Gambardella, Luca Maria (Dir.) ; Montemanni, Roberto (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2013 ; 2013INFO002.

In this thesis we discuss practical and theoretical aspects of various stochastic vehicle routing problems. These are combinatorial optimization problems related to the field of transportation and logistics in which input data is (partially) represented in a stochastic way. More in detail, we focus on two-stage stochastic vehicle routing problems and in particular on so-called a priori...

Università della Svizzera italiana

Teaching networks how to learn : reinforcement learning for data dissemination in wireless sensor networks

Förster, Anna ; Murphy, Amy L. (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2009 ; 2009INFO001.

Wireless sensor networks (WSNs) are a fast developing research area with many new exciting applications arising, ranging from micro climate and environmental monitoring through health and structural monitoring to interplanetary communications. At the same time researchers have invested a lot of time and effort into developing high performance energy efficient and reliable communication protocols...