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Lucassen, Max (author)
Least-squares support-vector-machines are a frequently used supervised learning method for nonlinear regression and classification. The method can be implemented by solving either its primal problem or dual problem. In the dual problem a linear system needs to be solved, yet for large-scale problems this can be impractical as current methods...
master thesis 2020
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Dominicus, S. (author)
The next generation of ground-based telescopes have a segmented primary mirror consisting of up to 800 segments which are mounted on a support truss. These segments are actively controlled to correct for external disturbances of which wind loading is the primary source. As mirror size and number of segments grows ever larger, dynamic coupling...
master thesis 2016
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Barak, R. (author)
The recent implementation of single electron quantum dots (QDs) in semiconductor hetero-structures as quantum bits (Qbits) [1] disclosed a promising route for the forthcoming creation of the first quantum computers based on a large set of Qbits. The scaling up of Qbits would indeed exhibit the full potential of quantum computation. Confinement...
master thesis 2015
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Nguyen Hoang Kien, N.H.K. (author)
In the regularization of ill-posed problems from image restoration, where we want to recover an image from blurred and noisy data, there are many methods that can be useful. Among those, the TRUSTmu method proposed in Rojas and Steihaug, 2002, is an efficient method for solving large-scale regularization problems with additional non-negativity...
master thesis 2014
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Aardenburg, W. (author)
Het huidige klimaat in Nederland voor het maken van grootschalige Leisure wordt geleid door een ontwikkelaars mentaliteit van korte termijn planning en snelle resultaten. Grond wordt op overzichtelijke wijze verkaveld en kan op deze manier voor op korte termijn ontwikkeld worden zonder dat er op een overzichtelijke manier een duidelijke visie...
master thesis 2008
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