Searched for: subject%3A%22tensor%255C+decomposition%22
(1 - 16 of 16)
document
Kerkhove, Casper (author)
The recent success of - and demand for - compliant mechanisms has increased rapidly within the micro-electromechanical systems-, aircraft-, spacecraft-, surgical-, and precision-instrument industries. Yet, even greater success may be achieved by overcoming the computational cost and instability of the mechanisms' design methodology. This...
master thesis 2023
document
Smeenk, Rutger (author)
This research aims at quantifying the uncertainty in the predictions of tensor network constrained kernel machines, focusing on the Canonical Polyadic Decomposition (CPD) constrained kernel machine. Constraining the parameters in the kernel machine optimization problem to be a CPD results in a linear computational complexity in the number of...
master thesis 2023
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Stunnenberg, Kenneth (author)
Brain disorders in children pose significant challenges to their development, impacting cognition, speech, movement, and behavior. The uncertainty surrounding prognostic information at the time of diagnosis leaves families with numerous questions about the future. The Child Brain Lab at Erasmus MC Sophia Children's Hospital conducts IQ,...
master thesis 2023
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de Heer, Owen (author)
Matrix multiplication with the standard algorithm has an algebraic complexity of O(n^3) for n x n matrices, but in 1969 Strassen found another algorithm for multiplying 2 x 2 matrices with which he showed that matrix multiplication can be done with a complexity of O(n^2.81) by applying his algorithm recursively for large...
bachelor thesis 2023
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Denarié, Pierre-Antoine (author)
Blind Source Separation (BSS), the separation of latent source components from observed mixtures, is relevant to many fields of expertise such as neuro-imaging, economics and machine learning. Reliable estimates of the sources can be obtained through diagonalization of the cumulant tensor, i.e., a fourth-order symmetric multi-linear array...
master thesis 2022
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Jonnalagadda, Aravind (author)
Natural Language Processing (NLP) deals with understanding and processing human text by any computer software. There are several network architectures in the fields of deep learning and artificial intelligence that are used for NLP. Deep learning techniques like recurrent neural networks and feed-forward neural networks are used to develop...
master thesis 2022
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van Mourik, Ewoud (author)
This thesis studies the Canonical Polyadic Decomposition (CPD) constrained kernel machine for large scale learning, i.e. learning with a large number of samples. The kernel machine optimization problem is solved in the primal space, such that the complexity of the problem scales linearly in the number of samples as opposed to scaling cubically...
master thesis 2022
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LI, Zhehan (author)
This thesis applies the Gauss-Newton optimizer to estimate the parameter values of the Volterra-PARAFAC model by minimizing a nonlinear least square cost (NLS) function given the input and output measurements of the MISO Volterra system.
master thesis 2022
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Menzen, C.M. (author), Kok, M. (author), Batselier, K. (author)
Multiway data often naturally occurs in a tensorial format which can be approximately represented by a low-rank tensor decomposition. This is useful because complexity can be significantly reduced and the treatment of large-scale data sets can be facilitated. In this paper, we find a low-rank representation for a given tensor by solving a...
journal article 2022
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Röhrig-Zöllner, Melven (author), Thies, J. (author), Basermann, Achim (author)
There are several factorizations of multidimensional tensors into lower-dimensional components, known as ``tensor networks."" We consider the popular ``tensor-train"" (TT) format and ask, How efficiently can we compute a low-rank approximation from a full tensor on current multicore CPUs? Compared to sparse and dense linear algebra, kernel...
journal article 2022
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de Rooij, S.J.S. (author)
In streaming video completion one aims to fill in missing pixels in streaming video data. This is a problem that naturally arises in the context of surveillance videos. Since these are streaming videos, they must be completed online and in real-time. This makes the streaming video completion problem significantly more difficult than the related...
master thesis 2020
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Karagöz, Ridvan (author)
B-splines are basis functions for the spline function space and are extensively used in applications requiring function approximation. The generalization of B-splines to multiple dimensions is done through tensor products of their univariate basis functions. The number of basis functions and weights that define a multivariate B-spline surface,...
master thesis 2020
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Gedon, Daniel (author)
For large-scale system with tens of thousands of states and outputs the computation in the conventional Kalman filter becomes time-consuming such that Kalman filtering in large-scale real-time application is practically infeasible. A possible mathematical framework to lift the curse of dimensionality is to lift the problem in higher dimensions...
master thesis 2019
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Gunes, Bilal (author)
doctoral thesis 2018
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Maswan, Jelimo (author)
Atrial fibrillation (AF) is one of the more common clinical arrhythmias with a high morbidity and mortality. Despite this, the electrophysiological and pathological mechanisms associated with AF largely remain a mystery, encouraging the use of ever more sophisticated techniques to extract vital information for diagnostic and therapeutic purposes...
master thesis 2017
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Insuasty, Edwin (author), van den Hof, P.M.J. (author), Weiland, Siep (author), Jansen, J.D. (author)
In reservoir engineering, it is attractive to characterize the difference between reservoir models in metrics that relate to the economic performance of the reservoir as well as to the underlying geological structure. In this paper, we develop a dissimilarity measure that is based on reservoir flow patterns under a particular operational...
journal article 2017
Searched for: subject%3A%22tensor%255C+decomposition%22
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