Ergebnisse einschränken

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...

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...

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...

An optimally concentrated Gabor transform for localized time-frequency components

Ricaud, Benjamin ; Stempfel, Guillaume ; Torrésani, Bruno ; Wiesmeyr, Christoph ; Lachambre, Hélène ; Onchis, Darian

In: Advances in Computational Mathematics, 2014, vol. 40, no. 3, p. 683-702

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...

Influence of detector collimation on SNR in four different MDCT scanners using a reconstructed slice thickness of 5mm

Verdun, F. ; Noel, A. ; Meuli, R. ; Pachoud, M. ; Monnin, P. ; Valley, J.-F ; Schnyder, P. ; Denys, A.

In: European Radiology, 2004, vol. 14, no. 10, p. 1866-1872

A survey on metaheuristics for stochastic combinatorial optimization

Bianchi, Leonora ; Dorigo, Marco ; Gambardella, Luca ; Gutjahr, Walter

In: Natural Computing, 2009, vol. 8, no. 2, p. 239-287

Design of tensegrity structures using parametric analysis and stochastic search

Rhode-Barbarigos, Landolf ; Jain, Himanshu ; Kripakaran, Prakash ; Smith, Ian

In: Engineering with Computers, 2010, vol. 26, no. 2, p. 193-203

An area and power optimization technique for CMOS bandgap voltage references

Tajalli, Armin ; Chahardori, Mohammad ; Khodaverdi, Abbas

In: Analog Integrated Circuits and Signal Processing, 2010, vol. 62, no. 2, p. 131-140

Conditioning DRASTIC model to simulate nitrate pollution case study: Hamadan-Bahar plain

Akhavan, Samira ; Mousavi, Sayed-Farhad ; Abedi-Koupai, Jahangir ; Abbaspour, Karim

In: Environmental Earth Sciences, 2011, vol. 63, no. 6, p. 1155-1167