Search for dissertations about: "non-convex optimization"

Showing result 1 - 5 of 41 swedish dissertations containing the words non-convex optimization.

2. 1. Non-Convex Methods for Compressed Sensing and Low-Rank Matrix Problems

   Author : Daniele Gerosa; Matematik (naturvetenskapliga fakulteten); []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; compressed sensing; Low-rank Approximation; phase retrieval; Non-convex optimization;

   Abstract : In this thesis we study functionals of the type \( \mathcal{K}_{f,A,\b}(\x)= \mathcal{Q}(f)(\x) + \|A\x - \b \| ^2 \), where \(A\) is a linear map, \(\b\) a measurements vector and \( \mathcal{Q} \) is a functional transform called \emph{quadratic envelope}; this object is a very close relative of the \emph{Lasry-Lions envelope} and its use is meant to regularize the functionals \(f\). Carlsson and Olsson investigated in earlier works the connections between the functionals \( \mathcal{K}_{f,A,\b}\) and their unregularized counterparts \(f(\x) + \|A\x - \b \| ^2 \). READ MORE

4. 2. Fast local optimization in decision analytic software

   Author : Xiasong Ding; Love Ekenberg; Mittuniversitetet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; bilinear programming; decision analysis; optimization; linear progamming; decision support systems; iterative method; Computer science; Datavetenskap;

   Abstract : In decision analysis, significant recognition has been given to the fact that requiring numerically precise information seems unrealistic for real-life decision situations, Despite the emergence of many modern apporaches, which attempt to handle imprecise estimates, concentration has focused more on representation and less on evaluation. Methods such as the DELTA method  challenged this issue by its evaluation framework that can accommodate both precision an imprecision, and thus pushes forward the disign of advanced dicision analysis systems. READ MORE

5. 3. Rank Reduction with Convex Constraints

   Author : Christian Grussler; Institutionen för reglerteknik; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; low-rank approximation; model reduction; non-convex optimization; Douglas-Rachford; matrix completion; overlapping norm; k-support norm; atomic norm;

   Abstract : This thesis addresses problems which require low-rank solutions under convex constraints. In particular, the focus lies on model reduction of positive systems, as well as finite dimensional optimization problems that are convex, apart from a low-rank constraint. READ MORE

6. 4. Contributions to Signal Processing for MRI

   Author : Marcus Björk; Peter Stoica; Andreas Jakobsson; Uppsala universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Parameter estimation; efficient estimation algorithms; non-convex optimization; multicomponent T2 relaxometry; artifact reduction; T2 mapping; denoising; phase estimation; RF design; MR thermometry; in-vivo brain; Elektroteknik med inriktning mot signalbehandling; Electrical Engineering with specialization in Signal Processing;

   Abstract : Magnetic Resonance Imaging (MRI) is an important diagnostic tool for imaging soft tissue without the use of ionizing radiation. Moreover, through advanced signal processing, MRI can provide more than just anatomical information, such as estimates of tissue-specific physical properties. READ MORE

7. 5. Numerical Algorithms for Optimization Problems in Genetical Analysis

   Author : Kateryna Mishchenko; Sverker Holmgren; Dmitrii Silvestrov; Lars Rönnegård; Ann-Charlotte Berglund Sonnhammer; Mälardalens högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Quantitative Trait Loci QTL ; restricted maximum likelihood REML ; variance components; average information AI matrix; Local optimization; Quasi-Newton method; Active Set method; Hessian approximation; BFGS update; Applied mathematics; Tillämpad matematik; Matematik tillämpad matematik;

   Abstract : The focus of this thesis is on numerical algorithms for efficient solution of QTL analysis problem in genetics.Firstly, we consider QTL mapping problems where a standard least-squares model is used for computing the model fit. READ MORE